diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..e551b1b63232744bccee8e6a255cde218da30d11 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor _adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::_adaptive_avg_pool2d_backward::call(grad_output, self); +} + +// aten::_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::_adaptive_avg_pool2d_backward_out::call(grad_output, self, out); +} +// aten::_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { + return at::_ops::_adaptive_avg_pool2d_backward_out::call(grad_output, self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..48f9e6a94bb6fd272c4e91ccc5f8a348fb6cd8ed --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d07f925bd2af937b062149e13badd68438073fc3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _adaptive_avg_pool3d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & _adaptive_avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_batch_dim.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_batch_dim.h new file mode 100644 index 0000000000000000000000000000000000000000..70d30b347d225219c26c15d3dfc32f9c49c85ec7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_batch_dim.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_add_batch_dim(Tensor self, int batch_dim, int level) -> Tensor +inline at::Tensor _add_batch_dim(const at::Tensor & self, int64_t batch_dim, int64_t level) { + return at::_ops::_add_batch_dim::call(self, batch_dim, level); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..27986887914c059e81fc304357f6bfc17508f5ba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _add_relu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _add_relu_outf(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97ece5bfd2d7cba3fac04076f1abc3719d8024f4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_meta_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & _add_relu_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _add_relu_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..28bf2b29f408a66e4cd0d29da15f50d1e3a61d51 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor add_relu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_relu_out(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & add_relu_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _add_relu_Scalar_out(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor add_relu(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_relu_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..caece26fb30cf6837706dc31f9d49fa684dddda5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple _aminmax_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self); +TORCH_API ::std::tuple _aminmax_outf(const at::Tensor & self, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple _aminmax_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple _aminmax_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1498519fc761e2d944fb66f9d5b1b9bf13b91fb2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _amp_foreach_non_finite_check_and_unscale_(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..085fb2b62ffaaa83ffa644646af5854c5c0e9397 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _amp_foreach_non_finite_check_and_unscale_ { + using schema = void (at::TensorList, at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_amp_foreach_non_finite_check_and_unscale_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_amp_foreach_non_finite_check_and_unscale_(Tensor(a!)[] self, Tensor(b!) found_inf, Tensor inv_scale) -> ()"; + static void call(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale); +}; + +struct TORCH_API _amp_foreach_non_finite_check_and_unscale_out { + using schema = void (at::TensorList, at::Tensor &, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_amp_foreach_non_finite_check_and_unscale"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale, at::TensorList out); +}; + +struct TORCH_API _amp_foreach_non_finite_check_and_unscale { + using schema = ::std::tuple<::std::vector,at::Tensor> (at::TensorList, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_amp_foreach_non_finite_check_and_unscale"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_amp_foreach_non_finite_check_and_unscale(Tensor[] self, Tensor found_inf, Tensor inv_scale) -> (Tensor[] self_out, Tensor found_inf_out)"; + static ::std::tuple<::std::vector,at::Tensor> call(at::TensorList self, const at::Tensor & found_inf, const at::Tensor & inv_scale); + static ::std::tuple<::std::vector,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & found_inf, const at::Tensor & inv_scale); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_update_scale_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_update_scale_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..473f40b4a57f2713825880f57d5c242d4451a9bc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_update_scale_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & _amp_update_scale_(at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_scalar_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_scalar_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bd629b09dff6009fa68a80bee85233bdb91a12aa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_scalar_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _assert_scalar { + using schema = void (const at::Scalar &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_assert_scalar"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_assert_scalar(Scalar self, str assert_msg) -> ()"; + static void call(const at::Scalar & self, c10::string_view assert_msg); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, c10::string_view assert_msg); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_autocast_to_full_precision_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_autocast_to_full_precision_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0954c034d3fcd2251d93c348af7a153095bee51f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_autocast_to_full_precision_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _autocast_to_full_precision(const at::Tensor & self, bool cuda_enabled, bool cpu_enabled); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf4b525ac41fde2e548db2adf43041f8e93886d9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API void _backward(const at::Tensor & self, at::TensorList inputs, const ::std::optional & gradient={}, ::std::optional retain_graph=::std::nullopt, bool create_graph=false); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_no_update.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_no_update.h new file mode 100644 index 0000000000000000000000000000000000000000..caf169fc868908bf7f24f3ee6818f11e105af58c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_no_update.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_batch_norm_no_update(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _batch_norm_no_update(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps) { + return at::_ops::_batch_norm_no_update::call(input, weight, bias, running_mean, running_var, momentum, eps); +} + +// aten::_batch_norm_no_update.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple _batch_norm_no_update_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps) { + return at::_ops::_batch_norm_no_update_out::call(input, weight, bias, running_mean, running_var, momentum, eps, out0, out1, out2, out3); +} +// aten::_batch_norm_no_update.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple _batch_norm_no_update_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::_batch_norm_no_update_out::call(input, weight, bias, running_mean, running_var, momentum, eps, out0, out1, out2, out3); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char_native.h new file mode 100644 index 0000000000000000000000000000000000000000..12883720942c874ab4d6755ead3051337bfe5163 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _cast_Char(const at::Tensor & self, bool non_blocking=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Double_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Double_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..29bb00d2ea76381c12dd04fd17c65bb999baddbd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Double_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _cast_Double(const at::Tensor & self, bool non_blocking=false); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Half_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Half_native.h new file mode 100644 index 0000000000000000000000000000000000000000..06a9516ff71d3bdda956a60e4b4a53869d7b6d9b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Half_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _cast_Half(const at::Tensor & self, bool non_blocking=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6fcb4d86e34cfce14f55a01b8899877832a4cc86 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _cdist_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist); +TORCH_API at::Tensor & _cdist_backward_outf(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7d2789cda325cb896cb70fb6c6894cbbf7650a54 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _cdist_forward_out(at::Tensor & out, const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); +TORCH_API at::Tensor & _cdist_forward_outf(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b4fcb28f70693c906e60d3f842b1b37d9d143004 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cdist_forward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cdist_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cdist_forward(Tensor x1, Tensor x2, float p, int? compute_mode) -> Tensor"; + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); +}; + +struct TORCH_API _cdist_forward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cdist_forward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_cdist_forward.out(Tensor x1, Tensor x2, float p, int? compute_mode, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..633a09fdfe6ff2dec598fe41cc4f7909b23fd005 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _chunk_cat(at::TensorList tensors, int64_t dim, int64_t num_chunks); +TORCH_API at::Tensor & _chunk_cat_out(at::Tensor & out, at::TensorList tensors, int64_t dim, int64_t num_chunks); +TORCH_API at::Tensor & _chunk_cat_outf(at::TensorList tensors, int64_t dim, int64_t num_chunks, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1ff19b1ef25984e32b9734707b8231ec392682d2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _chunk_cat { + using schema = at::Tensor (at::TensorList, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_chunk_cat"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_chunk_cat(Tensor[] tensors, int dim, int num_chunks) -> Tensor"; + static at::Tensor call(at::TensorList tensors, int64_t dim, int64_t num_chunks); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, int64_t dim, int64_t num_chunks); +}; + +struct TORCH_API _chunk_cat_out { + using schema = at::Tensor & (at::TensorList, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_chunk_cat"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_chunk_cat.out(Tensor[] tensors, int dim, int num_chunks, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::TensorList tensors, int64_t dim, int64_t num_chunks, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, int64_t dim, int64_t num_chunks, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced.h new file mode 100644 index 0000000000000000000000000000000000000000..5cff226c75fdaf9a7d5241304fc135bb2bfd2239 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _coalesced_out(at::Tensor & out, const at::Tensor & self, bool coalesced) { + return at::_ops::_coalesced_out::call(self, coalesced, out); +} +// aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _coalesced_outf(const at::Tensor & self, bool coalesced, at::Tensor & out) { + return at::_ops::_coalesced_out::call(self, coalesced, out); +} + +// aten::_coalesced(Tensor self, bool coalesced) -> Tensor +inline at::Tensor _coalesced(const at::Tensor & self, bool coalesced) { + return at::_ops::_coalesced::call(self, coalesced); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be36d4a51042b2317e1fc420f491c3d0240f06fb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _coalesced(const at::Tensor & self, bool coalesced); +TORCH_API at::Tensor & _coalesced_out(at::Tensor & out, const at::Tensor & self, bool coalesced); +TORCH_API at::Tensor & _coalesced_outf(const at::Tensor & self, bool coalesced, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..77d27890489bc3821ab6bb4316e8c353390b3c31 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _compute_linear_combination(const at::Tensor & input, const at::Tensor & coefficients); +TORCH_API at::Tensor & _compute_linear_combination_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & coefficients); +TORCH_API at::Tensor & _compute_linear_combination_outf(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_native.h new file mode 100644 index 0000000000000000000000000000000000000000..743a32b9d906763fe497057a3a0816fd2357ac4e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _compute_linear_combination(const at::Tensor & input, const at::Tensor & coefficients); +TORCH_API at::Tensor & _compute_linear_combination_out(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b1b2e9eda7762cff07888c8e44f7f139b11f78be --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _conj_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & _conj_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d51e2250ba2bec1ccd819a556ae4ec0cc3ae36f5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _conj_copy { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_conj_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_conj_copy(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _conj_copy_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_conj_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conv_depthwise2d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conv_depthwise2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36a9f2442af65418d8f8135339e6b3524fbf6aff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conv_depthwise2d_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _conv_depthwise2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); +TORCH_API at::Tensor _conv_depthwise2d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); +TORCH_API at::Tensor & _conv_depthwise2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); +TORCH_API at::Tensor & _conv_depthwise2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor & _conv_depthwise2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); +TORCH_API at::Tensor & _conv_depthwise2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conv_depthwise2d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conv_depthwise2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4004be60c0cb90c2a2cbff6da2d6bca73e722b6f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conv_depthwise2d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _conv_depthwise2d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_conv_depthwise2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_conv_depthwise2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); +}; + +struct TORCH_API _conv_depthwise2d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_conv_depthwise2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_conv_depthwise2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d73c59334ead4e1023077aa3dbc6d8f972dd1c32 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor _convert_indices_from_coo_to_csr(const at::Tensor & self, int64_t size, bool out_int32=false); +TORCH_API at::Tensor & _convert_indices_from_coo_to_csr_out(at::Tensor & out, const at::Tensor & self, int64_t size, bool out_int32=false); +TORCH_API at::Tensor & _convert_indices_from_coo_to_csr_outf(const at::Tensor & self, int64_t size, bool out_int32, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..000e41741551c82a2c2653b2f5e81cc38e117201 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _convert_weight_to_int4pack_for_cpu { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_convert_weight_to_int4pack_for_cpu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_convert_weight_to_int4pack_for_cpu(Tensor self, int innerKTiles) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t innerKTiles); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t innerKTiles); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9f1af5cf71aa5c059c687d602ef44442f503ba57 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _convert_weight_to_int4pack_cuda(const at::Tensor & self, int64_t innerKTiles); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode_native.h new file mode 100644 index 0000000000000000000000000000000000000000..572bc452c60ba6f452beb1ffe58c940d48e78ba5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _convolution_mode_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..aa1084d69c07929d4e7cdfdd5bd85b446cb9c62f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _convolution_mode { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::string_view, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_convolution_mode"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_convolution_mode(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, str padding, SymInt[] dilation, SymInt groups) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..885641dbb21a9489eda9adf1bebb324027e3fdb3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _ctc_loss_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor & _ctc_loss_backward_outf(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b6080fa9f7906aea5e1a8d8f002aacc742aa45e3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _ctc_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_backward_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss_backward"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ab5f11ba794852d76669a09d59e607455cc3cbe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d2c44f71d07d21b5e84b23ce7b8615c3e0cb4b7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _ctc_loss_out(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple ctc_loss_cpu(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple ctc_loss_gpu(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple ctc_loss_meta(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple _ctc_loss_Tensor_out(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple ctc_loss_tensor(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b4ecd806780ffe27269f9cff20ac79895290c097 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _ctc_loss { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_Tensor { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +}; + +struct TORCH_API _ctc_loss_Tensor_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..81260a2333292da71ddbec1ca352a055be3f730f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cudnn_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask) +inline ::std::tuple _cudnn_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); +} +namespace symint { + template >> + ::std::tuple _cudnn_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); + } +} + +// aten::_cudnn_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask) +inline ::std::tuple _cudnn_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); +} +namespace symint { + template >> + ::std::tuple _cudnn_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5a503d65ba1d2eaa098f002ed0799b29e6f42647 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, at::TensorOptions options); +TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn.h new file mode 100644 index 0000000000000000000000000000000000000000..1290445673496c49e04d2f5adeacb29670442e32 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state); + } +} + +// aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _cudnn_rnn_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_symint_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02dfab48736c65ed86ffae0c42b4bf71fbf89f0a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _cudnn_rnn_out_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +TORCH_API ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h new file mode 100644 index 0000000000000000000000000000000000000000..928d26c6067cd351fc281e00b948ded3f085c5e5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_clear_plan_cache(DeviceIndex device_index) -> () +inline void _cufft_clear_plan_cache(at::DeviceIndex device_index) { + return at::_ops::_cufft_clear_plan_cache::call(device_index); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size.h new file mode 100644 index 0000000000000000000000000000000000000000..a52157f65be2298de1d1c76e35533c9d7415c904 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_get_plan_cache_max_size(DeviceIndex device_index) -> int +inline int64_t _cufft_get_plan_cache_max_size(at::DeviceIndex device_index) { + return at::_ops::_cufft_get_plan_cache_max_size::call(device_index); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummax_helper_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummax_helper_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa685ddabfedfd6f7a391d0e7da066c5565cd60c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummax_helper_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API void _cummax_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a0e776f5b0e4a5f001bdf36e7e5bdc5d50f12af --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _cummin_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c9c59dc1f3bdab3c119045d162e235e21cd34c90 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void cummin_helper_cpu(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +TORCH_API void cummin_helper_cuda(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dim_arange_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dim_arange_native.h new file mode 100644 index 0000000000000000000000000000000000000000..750be6da9ef6f51708145a511fdc1bef90823ec3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dim_arange_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _dim_arange(const at::Tensor & like, int64_t dim); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..54a1dc563c8b19a87f495538ba6499ec3d6cb2d5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _dyn_quant_matmul_4bit_cpu(const at::Tensor & inp, const at::Tensor & packed_weights, int64_t block_size, int64_t in_features, int64_t out_features); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..38a3603d686962edc1f87b308c87edbe974a5661 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e854066f4967c44c831a937c816479d40a8926d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5eefe22fd8cc7395d7bd5261d869f9f2d3ccb097 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _embedding_bag_forward_only_out(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple _embedding_bag_forward_only_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +TORCH_API ::std::tuple _embedding_bag_forward_only_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..875564b98801ad2e644dcaf67ed368c73c33e120 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _embedding_bag_per_sample_weights_backward_out(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out); +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward_cpu(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward_cuda(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1ca17ea9befdd479bd66dea863bc488aa9e26fa0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _embedding_bag_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_sparse_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..58d3d3f6025067f8b56c4d6ac265e958ced10e5e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _embedding_bag_sparse_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..165f9aafe069cf7ef4b35be04d7ed7c2fb11c6b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _embedding_bag_sparse_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, bool, int64_t, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_sparse_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fdac4039218f036227f30964e210afeb524359f6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _empty_affine_quantized_out_symint(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor empty_affine_quantized_other_backends_stub(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6806a586c44e09b6e61773731c147f839c036cb9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _fake_quantize_learnable_per_tensor_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5f8d830cc6360ae2df1a33090c87053820e06048 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _fake_quantize_learnable_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c.h new file mode 100644 index 0000000000000000000000000000000000000000..25c47dd14878a472dfc2d7aed454025d9c982481 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor +inline at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward); +} +namespace symint { + template >> + at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward); + } +} + +// aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor +inline at::Tensor _fft_c2c_symint(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, dim, normalization, forward); +} +namespace symint { + template >> + at::Tensor _fft_c2c(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, dim, normalization, forward); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_symint_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2r.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2r.h new file mode 100644 index 0000000000000000000000000000000000000000..05de31e8a7e740eb156213087a4446a8ce4600f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2r.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template >> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template >> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_r2c_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_r2c_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80ca9c4276dd8ddb545a314ffa58883ff727e74a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_r2c_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fft_r2c { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_r2c"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fft_r2c(Tensor self, int[] dim, int normalization, bool onesided) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +}; + +struct TORCH_API _fft_r2c_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_r2c"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fft_r2c.out(Tensor self, int[] dim, int normalization, bool onesided, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8815cf4a5ff02cb3ea7c31d6e1883250b0e86480 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_meta_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_flash_attention_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_flash_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f22d632677fa3f0d81525698dd125f803c7b859a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_flash_attention_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _flash_attention_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymInt, double, bool, const at::Tensor &, const at::Tensor &, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_flash_attention_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor rng_state, Tensor unused, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4f62a900123112922c4c4437bf17f15ff7f06428 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _flash_attention_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, double, bool, bool, ::std::optional, ::std::optional, ::std::optional, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_flash_attention_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, bool return_debug_mask, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None, Tensor? seqused_k=None, Tensor? alibi_slopes=None) -> (Tensor output, Tensor softmax_logsumexp, Tensor rng_state, Tensor unused, Tensor debug_attn_mask)"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right, const ::std::optional & seqused_k, const ::std::optional & alibi_slopes); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right, const ::std::optional & seqused_k, const ::std::optional & alibi_slopes); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add.h new file mode 100644 index 0000000000000000000000000000000000000000..65504d2b58603369658746651102a5b20481ce0d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add.h @@ -0,0 +1,107 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_add.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_add_Scalar::call(self, scalar); +} + +// aten::_foreach_add_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_add_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_add__Scalar::call(self, scalar); +} + +// aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_List::call(self, other, alpha); +} + +// aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () +inline void _foreach_add_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add__List::call(self, other, alpha); +} + +// aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_add_ScalarList::call(self, scalars); +} + +// aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_add_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_add__ScalarList::call(self, scalars); +} + +// aten::_foreach_add.Tensor(Tensor[] self, Tensor other, *, Scalar alpha=1) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_Tensor::call(self, other, alpha); +} + +// aten::_foreach_add_.Tensor(Tensor(a!)[] self, Tensor other, *, Scalar alpha=1) -> () +inline void _foreach_add_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add__Tensor::call(self, other, alpha); +} + +// aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_add_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_add_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_List_out::call(self, other, alpha, out); +} +// aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out) { + return at::_ops::_foreach_add_List_out::call(self, other, alpha, out); +} + +// aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_add_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_add_ScalarList_out::call(self, scalars, out); +} + +// aten::_foreach_add.Tensor_out(Tensor[] self, Tensor other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_Tensor_out::call(self, other, alpha, out); +} +// aten::_foreach_add.Tensor_out(Tensor[] self, Tensor other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, at::TensorList out) { + return at::_ops::_foreach_add_Tensor_out::call(self, other, alpha, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c10d0ee812d27a0ba70137e4e7926627b5e7649 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_add(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_add_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_add(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector _foreach_add(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_add_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_add(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_asin_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_asin_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d4a3f5d8c82e738698a4c4ee7e9c0fd8108cde9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_asin_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_asin(at::TensorList self); +TORCH_API void _foreach_asin_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_asin_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_asin_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..806fb46ef53acf277f206188cce7f089b20d9133 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_atan(at::TensorList self); +TORCH_API void _foreach_atan_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max.h new file mode 100644 index 0000000000000000000000000000000000000000..56d90ca7e84b9fbf4ab5f6348c93d14c856c69e8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max.h @@ -0,0 +1,88 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_clamp_max(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_max_Scalar::call(self, scalar); +} + +// aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_clamp_max_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_max__Scalar::call(self, scalar); +} + +// aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_clamp_max(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_max_List::call(self, other); +} + +// aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_clamp_max_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_max__List::call(self, other); +} + +// aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_clamp_max(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_max_ScalarList::call(self, scalars); +} + +// aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_clamp_max_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_max__ScalarList::call(self, scalars); +} + +// aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_max_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_clamp_max_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_max_List_out::call(self, other, out); +} +// aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_clamp_max_List_out::call(self, other, out); +} + +// aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_max_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_clamp_max_ScalarList_out::call(self, scalars, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1b20a06a15d4b549daa6c942819ebfb8d404e666 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max_native.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_clamp_max_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_max_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_clamp_max_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_max_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_max_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_max_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_clamp_max_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_max_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_clamp_max_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_min_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_min_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5f68ca4e784f718aebe0807010b2a1358bf757e5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_min_ops.h @@ -0,0 +1,122 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_clamp_min_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_min__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_min_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_min__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_min_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_min__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_min_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_min_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_min_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_copy_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_copy_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3ab773fd9d3a3afa432ddc328b7a050ab5b856a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_copy_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _foreach_copy_(at::TensorList self, at::TensorList src, bool non_blocking=false); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cos_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cos_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fc1e1653a2861bc414b3ff625e5dc5c03891b153 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cos_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_cos { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cos"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cos(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cos_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cos_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cos_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cos_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cos"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_cos.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e3bd31e232b6c6102f5b17931b93808b1369c5bf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_cosh { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cosh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cosh(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cosh_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cosh_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cosh_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cosh_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cosh"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_div.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_div.h new file mode 100644 index 0000000000000000000000000000000000000000..dd52108fadfd18843dfa21dd274c6c694e2a70f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_div.h @@ -0,0 +1,107 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_div.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_div_Scalar::call(self, scalar); +} + +// aten::_foreach_div_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_div_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_div__Scalar::call(self, scalar); +} + +// aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_div_List::call(self, other); +} + +// aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_div_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_div__List::call(self, other); +} + +// aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_div_ScalarList::call(self, scalars); +} + +// aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_div_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_div__ScalarList::call(self, scalars); +} + +// aten::_foreach_div.Tensor(Tensor[] self, Tensor other) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_div_Tensor::call(self, other); +} + +// aten::_foreach_div_.Tensor(Tensor(a!)[] self, Tensor other) -> () +inline void _foreach_div_(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_div__Tensor::call(self, other); +} + +// aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_div_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_div_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_div_List_out::call(self, other, out); +} +// aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_div_List_out::call(self, other, out); +} + +// aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_div_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_div_ScalarList_out::call(self, scalars, out); +} + +// aten::_foreach_div.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_div_Tensor_out::call(self, other, out); +} +// aten::_foreach_div.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, const at::Tensor & other, at::TensorList out) { + return at::_ops::_foreach_div_Tensor_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_div_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_div_native.h new file mode 100644 index 0000000000000000000000000000000000000000..da38d2765fd2e259f584ffa2ff6482b1734cf135 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_div_native.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_div_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_div_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_div_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_div_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_div_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_div_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_div_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_div_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_div_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_div_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_div_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_div_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_div_tensor_kernel_slow(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_Tensor_out(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void foreach_tensor_div_tensor_kernel_slow_(at::TensorList self, const at::Tensor & other); +TORCH_API ::std::vector foreach_tensor_div_tensor_kernel_cuda(at::TensorList self, const at::Tensor & other); +TORCH_API void foreach_tensor_div_tensor_kernel_cuda_(at::TensorList self, const at::Tensor & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc.h new file mode 100644 index 0000000000000000000000000000000000000000..e08c1416b3ac471d499745939e79a4956aeee78f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_erfc(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_erfc(at::TensorList self) { + return at::_ops::_foreach_erfc::call(self); +} + +// aten::_foreach_erfc_(Tensor(a!)[] self) -> () +inline void _foreach_erfc_(at::TensorList self) { + return at::_ops::_foreach_erfc_::call(self); +} + +// aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erfc_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_erfc_out::call(self, out); +} +// aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erfc_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_erfc_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..98c3a2e937b8a2ffe1885133a4d421e9c8ded3cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_expm1(at::TensorList self); +TORCH_API void _foreach_expm1_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3ae99eca64892403a1be02b0d75a4f0d94964863 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_expm1_slow(at::TensorList self); +TORCH_API void _foreach_expm1_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_expm1_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_expm1_cuda(at::TensorList self); +TORCH_API void foreach_tensor_expm1_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eebf66a88b9303f4a283f2bdcb53087d63750d01 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_floor(at::TensorList self); +TORCH_API void _foreach_floor_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_floor_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_floor_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_frac_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_frac_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb4c773498213cd132e3a21e637e33a2c793d133 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_frac_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_frac(at::TensorList self); +TORCH_API void _foreach_frac_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lgamma_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lgamma_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2294cf599f2c68cc36c811e0d67fd5603352a848 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lgamma_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_lgamma_slow(at::TensorList self); +TORCH_API void _foreach_lgamma_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_lgamma_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_lgamma_cuda(at::TensorList self); +TORCH_API void foreach_tensor_lgamma_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log1p_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log1p_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d9e789da87cdf027fa8321f229dbeeece7d8364c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log1p_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_log1p_slow(at::TensorList self); +TORCH_API void _foreach_log1p_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_log1p_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_log1p_cuda(at::TensorList self); +TORCH_API void foreach_tensor_log1p_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2.h new file mode 100644 index 0000000000000000000000000000000000000000..6d40d8d6b0ec450bfdcf84c6481a390e0c23e681 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_log2(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log2(at::TensorList self) { + return at::_ops::_foreach_log2::call(self); +} + +// aten::_foreach_log2_(Tensor(a!)[] self) -> () +inline void _foreach_log2_(at::TensorList self) { + return at::_ops::_foreach_log2_::call(self); +} + +// aten::_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log2_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log2_out::call(self, out); +} +// aten::_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log2_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log2_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6a9bff3f7487e5be557a420d5b8e4dda41568c2d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_log2(at::TensorList self); +TORCH_API void _foreach_log2_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_log2_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_log2_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_max_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_max_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6bc4fdc506544a5b466b459255811545db59ad60 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_max_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_max { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_max"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_max(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_max_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_max"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_max.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum.h new file mode 100644 index 0000000000000000000000000000000000000000..67edb9b2d3523fde26f8b817455d53b47d5e18cd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum.h @@ -0,0 +1,88 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum_Scalar::call(self, scalar); +} + +// aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_maximum_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum__Scalar::call(self, scalar); +} + +// aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum_List::call(self, other); +} + +// aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_maximum_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum__List::call(self, other); +} + +// aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum_ScalarList::call(self, scalars); +} + +// aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_maximum_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum__ScalarList::call(self, scalars); +} + +// aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_maximum_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum_List_out::call(self, other, out); +} +// aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_maximum_List_out::call(self, other, out); +} + +// aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_maximum_ScalarList_out::call(self, scalars, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7c5d28c9df07cfdacc607620ce9afa840527d42 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_compositeexplicitautograd_dispatch.h @@ -0,0 +1,39 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_maximum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_maximum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_maximum_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_maximum_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_maximum_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_maximum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_maximum_(at::TensorList self, at::ArrayRef scalars); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_mul.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_mul.h new file mode 100644 index 0000000000000000000000000000000000000000..09b9a7b1f8432a612349a91830af61f66e455a56 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_mul.h @@ -0,0 +1,107 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_mul.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_mul_Scalar::call(self, scalar); +} + +// aten::_foreach_mul_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_mul_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_mul__Scalar::call(self, scalar); +} + +// aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_mul_List::call(self, other); +} + +// aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_mul_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_mul__List::call(self, other); +} + +// aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_mul_ScalarList::call(self, scalars); +} + +// aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_mul_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_mul__ScalarList::call(self, scalars); +} + +// aten::_foreach_mul.Tensor(Tensor[] self, Tensor other) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_mul_Tensor::call(self, other); +} + +// aten::_foreach_mul_.Tensor(Tensor(a!)[] self, Tensor other) -> () +inline void _foreach_mul_(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_mul__Tensor::call(self, other); +} + +// aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_mul_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_mul_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_mul_List_out::call(self, other, out); +} +// aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_mul_List_out::call(self, other, out); +} + +// aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_mul_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_mul_ScalarList_out::call(self, scalars, out); +} + +// aten::_foreach_mul.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_mul_Tensor_out::call(self, other, out); +} +// aten::_foreach_mul.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, const at::Tensor & other, at::TensorList out) { + return at::_ops::_foreach_mul_Tensor_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_mul_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_mul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..08e4083bd9ca0c19feb936dc12ff9d479b4478a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_mul_ops.h @@ -0,0 +1,155 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_mul_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_mul.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_mul__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_mul_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_mul_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_mul__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_mul_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_mul__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_mul_Tensor { + using schema = ::std::vector (at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_mul.Tensor(Tensor[] self, Tensor other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Tensor & other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other); +}; + +struct TORCH_API _foreach_mul__Tensor { + using schema = void (at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_mul_.Tensor(Tensor(a!)[] self, Tensor other) -> ()"; + static void call(at::TensorList self, const at::Tensor & other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other); +}; + +struct TORCH_API _foreach_mul_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_mul_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_mul_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_mul_Tensor_out { + using schema = void (at::TensorList, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_mul.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Tensor & other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1c45183ed06e94633ed342e36771685b3db53537 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_reciprocal { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_reciprocal"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_reciprocal(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_reciprocal_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_reciprocal_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_reciprocal_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_reciprocal_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_reciprocal"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba5c455767ba3bf8c08344f7a8033996041cab91 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_round(at::TensorList self); +TORCH_API void _foreach_round_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_round_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_round_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c3b0a66a2b396fac9a836926241e6e98ab24c2c0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_round(at::TensorList self); +TORCH_API void _foreach_round_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d93226a670962d88aeeddf61dfd93e28fbef2fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_rsqrt(at::TensorList self); +TORCH_API void _foreach_rsqrt_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_rsqrt_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_rsqrt_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ef3058248b2fe7dace813063e4f6f83dee8a87c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_rsqrt(at::TensorList self); +TORCH_API void _foreach_rsqrt_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e1e43d3fa41c64c986883aad3a441ad73837e85 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_sigmoid(at::TensorList self); +TORCH_API void _foreach_sigmoid_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sinh_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sinh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fb976f1731e41f605c3e881389ce9c3d526a842c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sinh_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_sinh_slow(at::TensorList self); +TORCH_API void _foreach_sinh_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sinh_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sinh_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sinh_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..309e4e16a89d9431a21db3ce73923d8b947ce90f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h @@ -0,0 +1,122 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_sub_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_sub.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_sub__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_sub_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_sub_List { + using schema = ::std::vector (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_sub__List { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> ()"; + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_sub_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_sub__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_sub_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_sub_List_out { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +}; + +struct TORCH_API _foreach_sub_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tan.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tan.h new file mode 100644 index 0000000000000000000000000000000000000000..985b48ac272d678734e51ed2a89bda5de6747c3f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tan.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_tan(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_tan(at::TensorList self) { + return at::_ops::_foreach_tan::call(self); +} + +// aten::_foreach_tan_(Tensor(a!)[] self) -> () +inline void _foreach_tan_(at::TensorList self) { + return at::_ops::_foreach_tan_::call(self); +} + +// aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tan_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_tan_out::call(self, out); +} +// aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tan_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_tan_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tanh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tanh.h new file mode 100644 index 0000000000000000000000000000000000000000..64d39aea5ceae758ba9a7807c933f164f6e0ca23 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tanh.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_tanh(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_tanh(at::TensorList self) { + return at::_ops::_foreach_tanh::call(self); +} + +// aten::_foreach_tanh_(Tensor(a!)[] self) -> () +inline void _foreach_tanh_(at::TensorList self) { + return at::_ops::_foreach_tanh_::call(self); +} + +// aten::_foreach_tanh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tanh_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_tanh_out::call(self, out); +} +// aten::_foreach_tanh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tanh_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_tanh_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_zero_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_zero_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4a9e8127571513f42f07c63d30e193e2a771314f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_zero_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector _foreach_zero(at::TensorList self); +TORCH_API void _foreach_zero_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_zero_slow_(at::TensorList self); +TORCH_API void foreach_tensor_zero_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_scalar_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_scalar_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b043faee8618cd4873bbf2dec283d7a6e2322da3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_scalar_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _functional_assert_scalar(const at::Scalar & self, c10::string_view assert_msg, const at::Tensor & dep_token); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..88e99aa666d5abcac9067d5a9cbb469c366a21af --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _functional_sym_constrain_range { + using schema = at::Tensor (const at::Scalar &, ::std::optional, ::std::optional, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_functional_sym_constrain_range"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_functional_sym_constrain_range(Scalar size, int? min, int? max, Tensor dep_token) -> Tensor"; + static at::Tensor call(const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9ec0f048e8e2592caf970d4c5b5f1f645a0dbe4e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_out(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API void _fused_adagrad_kernel_cpu_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_kernel_cuda_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_tensor_lr_out(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API void _fused_adagrad_kernel_cpu_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_kernel_cuda_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c405f213414bac9f4314d7e0e135bd7cb1715841 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_adagrad_ { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adagrad_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad__tensor_lr { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad_"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adagrad_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fused_adagrad.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +}; + +struct TORCH_API _fused_adagrad { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adagrad(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out, Tensor[] state_steps_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad_tensor_lr_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = "tensor_lr_out"; + static constexpr const char* schema_str = "_fused_adagrad.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +}; + +struct TORCH_API _fused_adagrad_tensor_lr { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adagrad.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector> call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static ::std::tuple<::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw.h new file mode 100644 index 0000000000000000000000000000000000000000..a61f027619b2a91c9a90bebfbd66b9b17fa6b757 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw.h @@ -0,0 +1,69 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_adamw_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adamw_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_adamw_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw__tensor_lr::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adamw_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adamw(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adamw.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_tensor_lr_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adamw.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adamw_tensor_lr_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adamw.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adamw(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_tensor_lr::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0d42c225a2ceda86df9415d9cf5924ff4f8bad3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API int64_t _fused_sdp_choice(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c952ad3b5af8c9d69705226fe50cf75ec93ca94 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _fw_primal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t level); +TORCH_API at::Tensor & _fw_primal_copy_outf(const at::Tensor & self, int64_t level, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8393df9dee2248d540eb77c90bc2ed9f2a82657f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _gather_sparse_backward(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback.h new file mode 100644 index 0000000000000000000000000000000000000000..0d7d86e9acd120e64c700872759d8055341fb160 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_grid_sampler_2d_cpu_fallback(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor +inline at::Tensor _grid_sampler_2d_cpu_fallback(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::_grid_sampler_2d_cpu_fallback::call(input, grid, interpolation_mode, padding_mode, align_corners); +} + +// aten::_grid_sampler_2d_cpu_fallback.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _grid_sampler_2d_cpu_fallback_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::_grid_sampler_2d_cpu_fallback_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} +// aten::_grid_sampler_2d_cpu_fallback.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _grid_sampler_2d_cpu_fallback_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) { + return at::_ops::_grid_sampler_2d_cpu_fallback_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..96144cae319b0bede01ea0dbebc38fb9dd428cae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple _grid_sampler_2d_cpu_fallback_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..68353e05715333e03fdbef227300a7abdd0dcd0b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _grid_sampler_2d_cpu_fallback_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4891535d6ea13ae9d35c4346bc22398a44719b9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _grid_sampler_2d_cpu_fallback_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grid_sampler_2d_cpu_fallback_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grouped_mm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grouped_mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8d31f98e372e127a36b66d2721a1d335e57834d2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grouped_mm_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _grouped_mm(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt); +TORCH_API at::Tensor _grouped_mm_cuda(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h new file mode 100644 index 0000000000000000000000000000000000000000..20a0af13aa410409b21edd06aa631d3b4ff06510 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool _has_same_storage_numel(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ddfbdf06414d0cc7133b58ddf1096dbf6f6f3a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b67ccd40d5c02591fd3ad51f9282b559d69c8343 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _index_put_impl_ { + using schema = at::Tensor & (at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_index_put_impl_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); +}; + +struct TORCH_API _index_put_impl_out { + using schema = at::Tensor & (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_index_put_impl"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out); +}; + +struct TORCH_API _index_put_impl { + using schema = at::Tensor (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_index_put_impl"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..33d93f1fd2de65e92b5129f8f2e7373399ab0072 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _indices_copy { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_indices_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_indices_copy(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _indices_copy_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_indices_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh.h new file mode 100644 index 0000000000000000000000000000000000000000..8f926459f5302a84f61cb819fe8f534f79520439 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_linalg_eigh(Tensor A, str UPLO="L", bool compute_v=True) -> (Tensor eigenvalues, Tensor eigenvectors) +inline ::std::tuple _linalg_eigh(const at::Tensor & A, c10::string_view UPLO="L", bool compute_v=true) { + return at::_ops::_linalg_eigh::call(A, UPLO, compute_v); +} + +// aten::_linalg_eigh.eigenvalues(Tensor A, str UPLO="L", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) +inline ::std::tuple _linalg_eigh_out(at::Tensor & eigenvalues, at::Tensor & eigenvectors, const at::Tensor & A, c10::string_view UPLO="L", bool compute_v=true) { + return at::_ops::_linalg_eigh_eigenvalues::call(A, UPLO, compute_v, eigenvalues, eigenvectors); +} +// aten::_linalg_eigh.eigenvalues(Tensor A, str UPLO="L", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) +inline ::std::tuple _linalg_eigh_outf(const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors) { + return at::_ops::_linalg_eigh_eigenvalues::call(A, UPLO, compute_v, eigenvalues, eigenvectors); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d190f8121e421e18c95f6bf9cafabd005bf277df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _linalg_eigh(const at::Tensor & A, c10::string_view UPLO="L", bool compute_v=true); +TORCH_API ::std::tuple _linalg_eigh_out(at::Tensor & eigenvalues, at::Tensor & eigenvectors, const at::Tensor & A, c10::string_view UPLO="L", bool compute_v=true); +TORCH_API ::std::tuple _linalg_eigh_outf(const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1504029de2cf3e92730aac36d1e6843a5a9047bd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _linalg_slogdet(const at::Tensor & A); +TORCH_API ::std::tuple _linalg_slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A); +TORCH_API ::std::tuple _linalg_slogdet_outf(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet, at::Tensor & LU, at::Tensor & pivots); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex.h new file mode 100644 index 0000000000000000000000000000000000000000..2bb785c5086759c5900f936dc4e22c08336e59c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor LU, Tensor pivots, Tensor info) +inline ::std::tuple _linalg_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false) { + return at::_ops::_linalg_solve_ex::call(A, B, left, check_errors); +} + +// aten::_linalg_solve_ex.result(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) +inline ::std::tuple _linalg_solve_ex_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info, const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false) { + return at::_ops::_linalg_solve_ex_result::call(A, B, left, check_errors, result, LU, pivots, info); +} +// aten::_linalg_solve_ex.result(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) +inline ::std::tuple _linalg_solve_ex_outf(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info) { + return at::_ops::_linalg_solve_ex_result::call(A, B, left, check_errors, result, LU, pivots, info); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..52440b8e74a6dac51699472dda35232d1bfdb573 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple _linalg_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a5505848a42ac74fd9dbb46e685ccd22de4c5ddb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured__linalg_solve_ex_out : public at::meta::structured__linalg_solve_ex { +void impl(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, const at::Tensor & result, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & info); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_svd_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_svd_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c480fc7c69d6ab0b3bef48042478d96182ce78a6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_svd_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _linalg_svd { + using schema = ::std::tuple (const at::Tensor &, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_linalg_svd"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_linalg_svd(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh)"; + static ::std::tuple call(const at::Tensor & A, bool full_matrices, bool compute_uv, ::std::optional driver); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool full_matrices, bool compute_uv, ::std::optional driver); +}; + +struct TORCH_API _linalg_svd_U { + using schema = ::std::tuple (const at::Tensor &, bool, bool, ::std::optional, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_linalg_svd"; + static constexpr const char* overload_name = "U"; + static constexpr const char* schema_str = "_linalg_svd.U(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh)"; + static ::std::tuple call(const at::Tensor & A, bool full_matrices, bool compute_uv, ::std::optional driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool full_matrices, bool compute_uv, ::std::optional driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_local_scalar_dense_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_local_scalar_dense_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..88014d1a605d41b814365f382df79ae497fcadfb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_local_scalar_dense_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Scalar _local_scalar_dense(const at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c572c56100c3aa0d970729558f101ffb8228fbd3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _log_softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +TORCH_API at::Tensor & _log_softmax_backward_data_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +TORCH_API at::Tensor & _log_softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fbaf742bc0904ef99d3e16938f1566021f0b15f2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _log_softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +TORCH_API at::Tensor & _log_softmax_backward_data_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +TORCH_API at::Tensor & _log_softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ad43c636a72fd962b80fd51acabc0d044e9333df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_log_softmax_backward_cpu_out : public at::meta::structured__log_softmax_backward_data { +void impl(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, const at::Tensor & out); +}; +struct TORCH_API structured_log_softmax_backward_cuda_out : public at::meta::structured__log_softmax_backward_data { +void impl(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8742c7a8e4d200226fc622deca2f8ecc2a6f9997 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _make_dual_copy(const at::Tensor & primal, const at::Tensor & tangent, int64_t level); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8383a2e8b600a5ea9ee92232bc0b60e3b8da9e06 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _make_per_channel_quantized_tensor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis); +TORCH_API at::Tensor & _make_per_channel_quantized_tensor_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..1ea1ecc9daf4898c1ea914fcef1dbdc31acb81a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_make_per_tensor_quantized_tensor(Tensor self, float scale, int zero_point) -> Tensor +inline at::Tensor _make_per_tensor_quantized_tensor(const at::Tensor & self, double scale, int64_t zero_point) { + return at::_ops::_make_per_tensor_quantized_tensor::call(self, scale, zero_point); +} + +// aten::_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_per_tensor_quantized_tensor_out(at::Tensor & out, const at::Tensor & self, double scale, int64_t zero_point) { + return at::_ops::_make_per_tensor_quantized_tensor_out::call(self, scale, zero_point, out); +} +// aten::_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_per_tensor_quantized_tensor_outf(const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out) { + return at::_ops::_make_per_tensor_quantized_tensor_out::call(self, scale, zero_point, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cde2f592ddee6a3e1d2606378f6d97558694d787 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _make_per_tensor_quantized_tensor_out(at::Tensor & out, const at::Tensor & self, double scale, int64_t zero_point); +TORCH_API at::Tensor & _make_per_tensor_quantized_tensor_outf(const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bcb38bb0e9868c094e8f68f4495c7e55ab8f553e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _make_per_tensor_quantized_tensor_out(const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out); +TORCH_API at::Tensor make_per_tensor_quantized_tensor_cpu(const at::Tensor & self, double scale, int64_t zero_point); +TORCH_API at::Tensor make_per_tensor_quantized_tensor_cuda(const at::Tensor & self, double scale, int64_t zero_point); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_scale_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_scale_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b95bb9a5cda0342a5422f11278f2c4466d65b9f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_scale_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _masked_scale(const at::Tensor & self, const at::Tensor & mask, double scale); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..10a76c12d2e89b0d3973eeb1d1dc52d7a8fef335 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _masked_softmax_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, ::std::optional dim=::std::nullopt); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_softmax_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cc92d5afde0f877330838534dd0c377adb92e376 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_masked_softmax_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _masked_softmax { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_masked_softmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_masked_softmax(Tensor self, Tensor mask, int? dim=None, int? mask_type=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mask, ::std::optional dim, ::std::optional mask_type); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, ::std::optional dim, ::std::optional mask_type); +}; + +struct TORCH_API _masked_softmax_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_masked_softmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_masked_softmax.out(Tensor self, Tensor mask, int? dim=None, int? mask_type=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mask, ::std::optional dim, ::std::optional mask_type, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, ::std::optional dim, ::std::optional mask_type, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mkldnn_transpose_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mkldnn_transpose_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..360cdba29e771b6b9c1d6cf3ae79e7533eb13097 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mkldnn_transpose_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _mkldnn_transpose { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_mkldnn_transpose"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_mkldnn_transpose(Tensor self, int dim0, int dim1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +struct TORCH_API _mkldnn_transpose_ { + using schema = at::Tensor & (at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_mkldnn_transpose_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_mkldnn_transpose_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +struct TORCH_API _mkldnn_transpose_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_mkldnn_transpose"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_mkldnn_transpose.out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..5865fd916668f38c3bd90ea17d107e6933ce4c6c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_mps_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _mps_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor _mps_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::_mps_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _mps_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution::call(self, weight, bias, padding, stride, dilation, groups); +} +namespace symint { + template >> + at::Tensor _mps_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution::call(self, weight, bias, padding, stride, dilation, groups); + } +} + +// aten::_mps_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::_mps_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::_mps_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); + } +} + +// aten::_mps_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::_mps_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..41a15aa5c7727a84409e6368a48798fa7f151d75 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_mps_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _mps_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor _mps_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::_mps_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _mps_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, padding, output_padding, stride, dilation, groups); +} +namespace symint { + template >> + at::Tensor _mps_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, padding, output_padding, stride, dilation, groups); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); +} +namespace symint { + template >> + at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5d5596a26cd605ef09b9b664a3a055a7d25ab158 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _mps_convolution_transpose_out_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8a66c0f1a185d73b557256ebbd84c5c631dbeb80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _mps_convolution_transpose { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_mps_convolution_transpose"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_mps_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API _mps_convolution_transpose_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_mps_convolution_transpose"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..57ab178108d3a34403ae4fa7b9da11cc03b41e49 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _native_batch_norm_legit_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +TORCH_API ::std::tuple _native_batch_norm_legit(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5731dd8f625c3c9b711b3bf785cd9e79229025f2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _native_multi_head_attention_out(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, bool need_weights, bool average_attn_weights, ::std::optional mask_type, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple native_multi_head_attention_cpu(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}, bool need_weights=true, bool average_attn_weights=true, ::std::optional mask_type=::std::nullopt); +TORCH_API ::std::tuple native_multi_head_attention_cuda(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}, bool need_weights=true, bool average_attn_weights=true, ::std::optional mask_type=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c180f471133d15492b812c11df755bab1cd4dc7e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _native_multi_head_attention { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_native_multi_head_attention"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, bool need_weights, bool average_attn_weights, ::std::optional mask_type); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, bool need_weights, bool average_attn_weights, ::std::optional mask_type); +}; + +struct TORCH_API _native_multi_head_attention_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, bool, bool, ::std::optional, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_native_multi_head_attention"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_native_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, bool need_weights, bool average_attn_weights, ::std::optional mask_type, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, bool need_weights, bool average_attn_weights, ::std::optional mask_type, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d85f4b622d0182bd0d4e87f5248034fd57cd5aac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _neg_view { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_neg_view"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_neg_view(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..90f605caed0912d32ba7155050473086420be1ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nested_from_padded { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_nested_from_padded"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nested_from_padded(Tensor padded, Tensor cpu_nested_shape_example, bool fuse_transform_0213=False) -> Tensor"; + static at::Tensor call(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213); +}; + +struct TORCH_API _nested_from_padded_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_nested_from_padded"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_nested_from_padded.out(Tensor padded, Tensor cpu_nested_shape_example, bool fuse_transform_0213=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_jagged_dummy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_jagged_dummy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0463f07d0019e4a3a7c2e520af1d14cb76e15912 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_jagged_dummy_native.h @@ -0,0 +1,25 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_lengths.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_lengths.h new file mode 100644 index 0000000000000000000000000000000000000000..525c10eb37721cae6db02db8fb87680aabe91f02 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_lengths.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_nested_get_lengths(Tensor self) -> Tensor +inline at::Tensor _nested_get_lengths(const at::Tensor & self) { + return at::_ops::_nested_get_lengths::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_max_seqlen_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_max_seqlen_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0463f07d0019e4a3a7c2e520af1d14cb76e15912 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_max_seqlen_native.h @@ -0,0 +1,25 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_sum_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_sum_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5d2be574bd1e02ed0ffe6523087caa653dd9e14c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_sum_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _nested_sum_backward_cpu(const at::Tensor & grad, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aee62dce8c13cfcfd660b84a38340405acd7334a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _nested_view_from_jagged_copy_out(const at::Tensor & self, const at::Tensor & offsets, const at::Tensor & dummy, const ::std::optional & lengths, int64_t ragged_idx, const ::std::optional & min_seqlen, const ::std::optional & max_seqlen, at::Tensor & out); +TORCH_API at::Tensor _nested_view_from_jagged_copy(const at::Tensor & self, const at::Tensor & offsets, const at::Tensor & dummy, const ::std::optional & lengths={}, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_available_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_available_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da44a324a595fe49afbcd31c355bc7f9bdc124f0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_available_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API bool _nnpack_available(); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..71ef1e732c127bf0cb29b35906ee29c0cd622f96 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _nnpack_spatial_convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride=1); +TORCH_API at::Tensor & _nnpack_spatial_convolution_out_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c7b1903263cad251ec626cd81a75097531fa5bf5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nnpack_spatial_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_nnpack_spatial_convolution"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride); +}; + +struct TORCH_API _nnpack_spatial_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_nnpack_spatial_convolution"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnz_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnz_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..15b6eb465104a3fc8090fe0f1d5f18b85e4297de --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnz_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nnz { + using schema = int64_t (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_nnz"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nnz(Tensor self) -> int"; + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e29638f0965e499296f18a24b0c8e080ce35bdf0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _pack_padded_sequence { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pack_padded_sequence"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_pack_padded_sequence(Tensor input, Tensor lengths, bool batch_first) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & lengths, bool batch_first); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & lengths, bool batch_first); +}; + +struct TORCH_API _pack_padded_sequence_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pack_padded_sequence"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_pack_padded_sequence.out(Tensor input, Tensor lengths, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & lengths, bool batch_first, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & lengths, bool batch_first, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_circular_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_circular_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..67d143bd325af7fd481da5d16e3dd509d4cad56c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_circular_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _pad_circular(const at::Tensor & self, at::IntArrayRef pad); +TORCH_API at::Tensor _pad_circular_symint(const at::Tensor & self, c10::SymIntArrayRef pad); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_circular_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_circular_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7fc87187a45ee978b47286c6a62ea42af0521870 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_circular_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _pad_circular { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pad_circular"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_pad_circular(Tensor self, SymInt[] pad) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef pad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5ef1ef969bf05f7a92fe2e06a1efd5ba520822ea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _padded_dense_to_jagged_forward { + using schema = at::Tensor (const at::Tensor &, at::TensorList, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_padded_dense_to_jagged_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_padded_dense_to_jagged_forward(Tensor dense, Tensor[] offsets, SymInt? total_L=None) -> Tensor"; + static at::Tensor call(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ae773bd7d5b671669035611a14696b38a1275505 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _pdist_forward_out(const at::Tensor & self, double p, at::Tensor & out); +TORCH_API at::Tensor _pdist_forward(const at::Tensor & self, double p=2); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1f2ee185b63907eae75cd74140adcb00f47beeb9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _pdist_forward { + using schema = at::Tensor (const at::Tensor &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pdist_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_pdist_forward(Tensor self, float p=2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, double p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p); +}; + +struct TORCH_API _pdist_forward_out { + using schema = at::Tensor & (const at::Tensor &, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pdist_forward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory.h new file mode 100644 index 0000000000000000000000000000000000000000..34507227aa5d73287f07b190b8bc8ef919954224 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_pin_memory(Tensor self, Device? device=None) -> Tensor +inline at::Tensor _pin_memory(const at::Tensor & self, ::std::optional device=::std::nullopt) { + return at::_ops::_pin_memory::call(self, device); +} + +// aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _pin_memory_out(at::Tensor & out, const at::Tensor & self, ::std::optional device=::std::nullopt) { + return at::_ops::_pin_memory_out::call(self, device, out); +} +// aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _pin_memory_outf(const at::Tensor & self, ::std::optional device, at::Tensor & out) { + return at::_ops::_pin_memory_out::call(self, device, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..27212e656d2c686f53c24de9d6cd5031bf904349 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _prelu_kernel_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_prelu_kernel_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_print_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_print_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e85728ec26480e5cd20ea8c052e4ec92cbe768d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_print_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void _print(c10::string_view s); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..946034a517f77d4444d99cbe1fe65f67ba66c352 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void _propagate_xla_data(const at::Tensor & input, const at::Tensor & output); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_alias_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_alias_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4a5916d3707c69a5e5e2b781d49c98a656ec2fb8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_alias_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _reshape_alias { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_reshape_alias"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_reshape_alias(Tensor(a) self, SymInt[] size, SymInt[] stride) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d1f6b3cd858364bb9029239659f745060270d6c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _reshape_copy(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor _reshape_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_rowwise_prune_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_rowwise_prune_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e83010c8e8b4fb676792e31c1a35d0a608588110 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_rowwise_prune_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _rowwise_prune { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_rowwise_prune"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_rowwise_prune(Tensor weight, Tensor mask, ScalarType compressed_indices_dtype) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet.h new file mode 100644 index 0000000000000000000000000000000000000000..3b4179a9a24e4dec6b8395948a4c1c46e01f1dbf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sample_dirichlet(Tensor self, Generator? generator=None) -> Tensor +inline at::Tensor _sample_dirichlet(const at::Tensor & self, ::std::optional generator=::std::nullopt) { + return at::_ops::_sample_dirichlet::call(self, generator); +} + +// aten::_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sample_dirichlet_out(at::Tensor & out, const at::Tensor & self, ::std::optional generator=::std::nullopt) { + return at::_ops::_sample_dirichlet_out::call(self, generator, out); +} +// aten::_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sample_dirichlet_outf(const at::Tensor & self, ::std::optional generator, at::Tensor & out) { + return at::_ops::_sample_dirichlet_out::call(self, generator, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1ac3f836fe66fb9b10d0b7e323cff5e189096eb6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple _scaled_dot_product_attention_math(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, const ::std::optional & dropout_mask={}, ::std::optional scale=::std::nullopt, bool enable_gqa=false); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_for_mps_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_for_mps_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..861dd2ef7a38cd653bb5fbc2c0aafd1a1e72a8c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_for_mps_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _scaled_dot_product_attention_math_for_mps { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, double, bool, const ::std::optional &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_scaled_dot_product_attention_math_for_mps"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_scaled_dot_product_attention_math_for_mps(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None, *, float? scale=None) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, const ::std::optional & dropout_mask, ::std::optional scale); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, const ::std::optional & dropout_mask, ::std::optional scale); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..482341f6dcac4eec84952e5fc4d8f47d4d173ea3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _scaled_dot_product_cudnn_attention_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymInt, double, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_scaled_dot_product_cudnn_attention_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_scaled_dot_product_cudnn_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, Tensor attn_bias, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, *, float? scale=None) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & philox_seed, const at::Tensor & philox_offset, const at::Tensor & attn_bias, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, ::std::optional scale); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & philox_seed, const at::Tensor & philox_offset, const at::Tensor & attn_bias, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, ::std::optional scale); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1cf0179574af0a70bab4e5bc71f10c3ff0d65fd7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _scaled_dot_product_efficient_attention_cuda(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt); +TORCH_API ::std::tuple _scaled_dot_product_efficient_attention_nestedtensor_cuda(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d7e4d85e0c0fa9589b11b0d6e858a32752de9e0d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _scaled_dot_product_flash_attention_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymInt, double, bool, const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_scaled_dot_product_flash_attention_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor philox_seed, Tensor philox_offset, *, float? scale=None) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2fe1a4c7aecef2ddb3655a34a879343aeb342956 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _scaled_dot_product_fused_attention_overrideable(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias={}, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..3833357616c2444570c08ae97cd1937be0a8adff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_scaled_grouped_mm(Tensor self, Tensor mat2, Tensor scale_a, Tensor scale_b, Tensor? offs=None, Tensor? bias=None, Tensor? scale_result=None, ScalarType? out_dtype=None, bool use_fast_accum=False) -> Tensor +inline at::Tensor _scaled_grouped_mm(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & offs={}, const ::std::optional & bias={}, const ::std::optional & scale_result={}, ::std::optional out_dtype=::std::nullopt, bool use_fast_accum=false) { + return at::_ops::_scaled_grouped_mm::call(self, mat2, scale_a, scale_b, offs, bias, scale_result, out_dtype, use_fast_accum); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm_v2_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm_v2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..71f58d1b2c9c0c82c8c26a56bbb9c4260b91ab9d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm_v2_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _scaled_grouped_mm_cuda_v2(const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt, at::IntArrayRef contraction_dim={}, bool use_fast_accum=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_mm_v2_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_mm_v2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..627d23b1f4321eab97a0cf79a5482719116f4141 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_mm_v2_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _scaled_mm_cuda_v2(const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional & bias, ::std::optional out_dtype, at::IntArrayRef contraction_dim={}, bool use_fast_accum=false); +TORCH_API at::Tensor & _scaled_mm_cuda_v2_out(const at::Tensor & self, const at::Tensor & mat2, at::TensorList scale_a, at::IntArrayRef recipe_a, at::IntArrayRef swizzle_a, at::TensorList scale_b, at::IntArrayRef recipe_b, at::IntArrayRef swizzle_b, const ::std::optional & bias, ::std::optional out_dtype, at::IntArrayRef contraction_dim, bool use_fast_accum, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_shape_as_tensor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_shape_as_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..46facae600620f4b62fcc980c854d194b90e1b03 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_shape_as_tensor_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _shape_as_tensor(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_forward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9ecb42910d2beacebd87847ecd466dfd00dbe015 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_forward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _slow_conv2d_forward_output { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_slow_conv2d_forward"; + static constexpr const char* overload_name = "output"; + static constexpr const char* schema_str = "_slow_conv2d_forward.output(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) output) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & output); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & output); +}; + +struct TORCH_API _slow_conv2d_forward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_slow_conv2d_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_slow_conv2d_forward(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_draw_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_draw_native.h new file mode 100644 index 0000000000000000000000000000000000000000..020a3082b22991f9cba7803579126cd703cec672 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_draw_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _sobol_engine_draw(const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, ::std::optional dtype); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_scramble.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_scramble.h new file mode 100644 index 0000000000000000000000000000000000000000..6078878c44f54477ef45073606d84b1386a6d8bc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_scramble.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sobol_engine_scramble_(Tensor(a!) self, Tensor ltm, int dimension) -> Tensor(a!) +inline at::Tensor & _sobol_engine_scramble_(at::Tensor & self, const at::Tensor & ltm, int64_t dimension) { + return at::_ops::_sobol_engine_scramble_::call(self, ltm, dimension); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data.h new file mode 100644 index 0000000000000000000000000000000000000000..2f135c72946863edc53594cfe1497919b26277c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_softmax_backward_data(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype) -> Tensor +inline at::Tensor _softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype) { + return at::_ops::_softmax_backward_data::call(grad_output, output, dim, input_dtype); +} + +// aten::_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _softmax_backward_data_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype) { + return at::_ops::_softmax_backward_data_out::call(grad_output, output, dim, input_dtype, grad_input); +} +// aten::_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & grad_input) { + return at::_ops::_softmax_backward_data_out::call(grad_output, output, dim, input_dtype, grad_input); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..320e141bdcaeb920bf388a076d7df43298aae9a3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +TORCH_API at::Tensor & _softmax_backward_data_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +TORCH_API at::Tensor & _softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm.h new file mode 100644 index 0000000000000000000000000000000000000000..995b92d71515640ae7645d72c4d16f186c22dccf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor _sparse_addmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::_sparse_addmm::call(self, mat1, mat2, beta, alpha); +} + +// aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_addmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::_sparse_addmm_out::call(self, mat1, mat2, beta, alpha, out); +} +// aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_addmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::_sparse_addmm_out::call(self, mat1, mat2, beta, alpha, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c805d941a6d4207091d886e174931faabe9d8b81 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _sparse_addmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _sparse_addmm_out(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aaf1a20e2d334e033e96dc9be8b3b1352fed9e08 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _sparse_broadcast_to_copy(const at::Tensor & self, at::IntArrayRef size); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8db6652ce1728ab98aa25b3e78500fad3a88f630 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_broadcast_to_copy { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_broadcast_to_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_broadcast_to_copy(Tensor self, int[] size) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size); +}; + +struct TORCH_API _sparse_broadcast_to_copy_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_broadcast_to_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe.h new file mode 100644 index 0000000000000000000000000000000000000000..6b80647b6e2477cad4a87badf68cc98f0128fe8f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_bsc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_bsc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_bsc_tensor_unsafe::call(ccol_indices, row_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_sparse_bsc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_bsc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_bsc_tensor_unsafe::call(ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c8904318ac09d06dfc2675dcfbb4cf0110902f4d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_with_dims_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_with_dims_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0dc46dc9bd7327867045692a735a7d6268e27f51 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_with_dims_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_compressed_tensor_with_dims { + using schema = at::Tensor (int64_t, int64_t, at::IntArrayRef, at::IntArrayRef, at::ScalarType, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_compressed_tensor_with_dims"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_compressed_tensor_with_dims(int nnz, int dense_dim, int[] size, int[] blocksize, ScalarType index_dtype, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor"; + static at::Tensor call(int64_t nnz, int64_t dense_dim, at::IntArrayRef size, at::IntArrayRef blocksize, at::ScalarType index_dtype, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t nnz, int64_t dense_dim, at::IntArrayRef size, at::IntArrayRef blocksize, at::ScalarType index_dtype, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44012b176eae1299d0e6052d6b3d75b2782edcc5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1da69bdf7a6b9b812b90be152e90c16ba37d4938 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _sparse_coo_tensor_with_dims_out(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor new_with_dims_sparse(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1b0d37b46063787b42d3cd1802e88bd2d9b92ad5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _sparse_csc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_tensor_unsafe.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_tensor_unsafe.h new file mode 100644 index 0000000000000000000000000000000000000000..6ce3c98ea902116f64a88ff06eca025aa54dd6f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_tensor_unsafe.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_csr_tensor_unsafe(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_csr_tensor_unsafe::call(crow_indices, col_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_csr_tensor_unsafe(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_csr_tensor_unsafe::call(crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_log_softmax_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_log_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9d5db02db2381c6ad24205ff14e29c66be4c1c3f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_log_softmax_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_log_softmax_int { + using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_log_softmax"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "_sparse_log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional dtype); +}; + +struct TORCH_API _sparse_log_softmax_Dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_log_softmax"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "_sparse_log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, ::std::optional dtype); +}; + +struct TORCH_API _sparse_log_softmax { + using schema = at::Tensor (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_log_softmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, bool half_to_float); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float); +}; + +struct TORCH_API _sparse_log_softmax_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_log_softmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_sparse_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8b1a0f1c0d10c99980327714c2b9125229965b20 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _sparse_mask_projection_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches=false); +TORCH_API at::Tensor & _sparse_mask_projection_outf(const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a1105cc1739b72405197eea353e20e5fb1d724c6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _sparse_semi_structured_apply_dense(const at::Tensor & input, const at::Tensor & thread_masks); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e6f7a744d9c7c94f0d771b82faa9d17990dfb49c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _sparse_semi_structured_mm(const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, ::std::optional out_dtype=::std::nullopt); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1faf632a5c8c0fd117dcb61219c70f7a40f0fbf8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _sparse_softmax_backward_data_out(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor softmax_backward_sparse_cpu(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +TORCH_API at::Tensor softmax_backward_sparse_cuda(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1fb4bbc241c340a741301a08cd839160b9954de7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_softmax_int { + using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_softmax"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "_sparse_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional dtype); +}; + +struct TORCH_API _sparse_softmax_Dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_softmax"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "_sparse_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, ::std::optional dtype); +}; + +struct TORCH_API _sparse_softmax { + using schema = at::Tensor (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_softmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_softmax(Tensor self, int dim, bool half_to_float) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, bool half_to_float); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float); +}; + +struct TORCH_API _sparse_softmax_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_softmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul.h new file mode 100644 index 0000000000000000000000000000000000000000..f3b1889bae6a341b61947cbe2914587c66dfd870 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor +inline at::Tensor _sparse_sparse_matmul(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::_sparse_sparse_matmul::call(self, other); +} + +// aten::_sparse_sparse_matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_sparse_matmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::_sparse_sparse_matmul_out::call(self, other, out); +} +// aten::_sparse_sparse_matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_sparse_matmul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::_sparse_sparse_matmul_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_ambiguous_defaults.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_ambiguous_defaults.h new file mode 100644 index 0000000000000000000000000000000000000000..bb4bae7d3ed2263ab319a50b4ea2164a08280c51 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_ambiguous_defaults.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_test_ambiguous_defaults.a(Tensor dummy, int a=1, int b=1) -> Tensor +inline at::Tensor _test_ambiguous_defaults(const at::Tensor & dummy, int64_t a=1, int64_t b=1) { + return at::_ops::_test_ambiguous_defaults_a::call(dummy, a, b); +} + +// aten::_test_ambiguous_defaults.b(Tensor dummy, int a=2, str b="2") -> Tensor +inline at::Tensor _test_ambiguous_defaults(const at::Tensor & dummy, int64_t a, c10::string_view b) { + return at::_ops::_test_ambiguous_defaults_b::call(dummy, a, b); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0f49d9949148152f099a0e2578b9a35e882a6f98 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _test_autograd_multiple_dispatch_view_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _test_autograd_multiple_dispatch_view_copy(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5de3a8f5915869e197dd329ebf39930cce96f283 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _test_functorch_fallback(const at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_floatlist.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_floatlist.h new file mode 100644 index 0000000000000000000000000000000000000000..7b9976404aacabf4af3d803ad4ab0c4103d0b1cd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_floatlist.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_test_optional_floatlist(Tensor values, float[]? addends) -> Tensor +inline at::Tensor _test_optional_floatlist(const at::Tensor & values, ::std::optional> addends) { + return at::_ops::_test_optional_floatlist::call(values, addends); +} + +// aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_optional_floatlist_out(at::Tensor & out, const at::Tensor & values, ::std::optional> addends) { + return at::_ops::_test_optional_floatlist_out::call(values, addends, out); +} +// aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_optional_floatlist_outf(const at::Tensor & values, ::std::optional> addends, at::Tensor & out) { + return at::_ops::_test_optional_floatlist_out::call(values, addends, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_floatlist_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_floatlist_native.h new file mode 100644 index 0000000000000000000000000000000000000000..52a299370b9afbce827ddf2f9510a6fc5f2ba8b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_floatlist_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _test_optional_floatlist_out(const at::Tensor & values, ::std::optional> addends, at::Tensor & out); +TORCH_API at::Tensor _test_optional_floatlist(const at::Tensor & values, ::std::optional> addends); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_string_default_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_string_default_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5cdae72536cddaf78e1d1c42c76cb1f990564dbc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_string_default_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _test_string_default(const at::Tensor & dummy, c10::string_view a="\"'\\", c10::string_view b="\"'\\"); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_warn_in_autograd_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_warn_in_autograd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..552e2b44d1821efc08cffc820fc1130c5cd0dfa9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_warn_in_autograd_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _test_warn_in_autograd(const at::Tensor & self); +TORCH_API at::Tensor & _test_warn_in_autograd_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_gru_cell_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_gru_cell_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..82c7c9509978411887397fa3011315ff8754870c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_gru_cell_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _thnn_differentiable_gru_cell_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_thnn_differentiable_gru_cell_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_thnn_differentiable_gru_cell_backward(Tensor grad_hy, Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias, Tensor? hidden_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_hy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_hy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..f211cc24353fbc9c7475698dc45393b0e571e12a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_thnn_fused_gru_cell(Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias=None, Tensor? hidden_bias=None) -> (Tensor, Tensor) +inline ::std::tuple _thnn_fused_gru_cell(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}) { + return at::_ops::_thnn_fused_gru_cell::call(input_gates, hidden_gates, hx, input_bias, hidden_bias); +} + +// aten::_thnn_fused_gru_cell.out(Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias=None, Tensor? hidden_bias=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _thnn_fused_gru_cell_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}) { + return at::_ops::_thnn_fused_gru_cell_out::call(input_gates, hidden_gates, hx, input_bias, hidden_bias, out0, out1); +} +// aten::_thnn_fused_gru_cell.out(Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias=None, Tensor? hidden_bias=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _thnn_fused_gru_cell_outf(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_thnn_fused_gru_cell_out::call(input_gates, hidden_gates, hx, input_bias, hidden_bias, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2e1b161cfff7e7a8225b59ebf12ee2c0299a4fc4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _thnn_fused_gru_cell_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_thnn_fused_gru_cell_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias); +}; + +struct TORCH_API _thnn_fused_gru_cell_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_thnn_fused_gru_cell_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))"; + static ::std::tuple call(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d3bc9734e0e6cb917c48a22e8697231fc1110f89 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _thnn_fused_gru_cell_out(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple _thnn_fused_gru_cell_cuda(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_impl_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_impl_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ff76547ff84bfa7a3e55868773e3cdbf5a493bb1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_impl_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _thnn_fused_lstm_cell_backward_impl { + using schema = ::std::tuple (const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_thnn_fused_lstm_cell_backward_impl"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_thnn_fused_lstm_cell_backward_impl(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias); +}; + +struct TORCH_API _thnn_fused_lstm_cell_backward_impl_out { + using schema = ::std::tuple (const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_thnn_fused_lstm_cell_backward_impl"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_thnn_fused_lstm_cell_backward_impl.out(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_dense.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_dense.h new file mode 100644 index 0000000000000000000000000000000000000000..dc8a6f67830604307789c371d3a7936d84e0ba75 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_dense.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_to_dense.out(Tensor self, ScalarType? dtype=None, bool? masked_grad=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_dense_out(at::Tensor & out, const at::Tensor & self, ::std::optional dtype=::std::nullopt, ::std::optional masked_grad=::std::nullopt) { + return at::_ops::_to_dense_out::call(self, dtype, masked_grad, out); +} +// aten::_to_dense.out(Tensor self, ScalarType? dtype=None, bool? masked_grad=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_dense_outf(const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad, at::Tensor & out) { + return at::_ops::_to_dense_out::call(self, dtype, masked_grad, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_dense_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_dense_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1fd4a4b8ef047f76619637a6ca909dfccfe29ccd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_dense_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _to_dense { + using schema = at::Tensor (const at::Tensor &, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_to_dense"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_to_dense(Tensor self, ScalarType? dtype=None, bool? masked_grad=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad); +}; + +struct TORCH_API _to_dense_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_to_dense"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_to_dense.out(Tensor self, ScalarType? dtype=None, bool? masked_grad=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsc_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e4e0c4bb494f83856042a4f064814db1ee848d1d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsc_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _to_sparse_bsc(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::std::nullopt); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr.h new file mode 100644 index 0000000000000000000000000000000000000000..bfe3201138f9c7e315de16551794f16000d08bbc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_bsr_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::std::nullopt) { + return at::_ops::_to_sparse_bsr_out::call(self, blocksize, dense_dim, out); +} +// aten::_to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_bsr_outf(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out) { + return at::_ops::_to_sparse_bsr_out::call(self, blocksize, dense_dim, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cfb3cb03ff9a8114fd6e4c087e6915f18cbd93c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _to_sparse_bsr(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::std::nullopt); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e2868e8e377f2b632f5fab3d5c0e2682fcab210 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _to_sparse_semi_structured(const at::Tensor & dense); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv.h new file mode 100644 index 0000000000000000000000000000000000000000..40b44a428eb475f72f3049462354e52e413d3dad --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_transform_bias_rescale_qkv(Tensor qkv, Tensor qkv_bias, int num_heads) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _transform_bias_rescale_qkv(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads) { + return at::_ops::_transform_bias_rescale_qkv::call(qkv, qkv_bias, num_heads); +} + +// aten::_transform_bias_rescale_qkv.out(Tensor qkv, Tensor qkv_bias, int num_heads, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _transform_bias_rescale_qkv_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads) { + return at::_ops::_transform_bias_rescale_qkv_out::call(qkv, qkv_bias, num_heads, out0, out1, out2); +} +// aten::_transform_bias_rescale_qkv.out(Tensor qkv, Tensor qkv_bias, int num_heads, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _transform_bias_rescale_qkv_outf(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::_transform_bias_rescale_qkv_out::call(qkv, qkv_bias, num_heads, out0, out1, out2); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d786066d695ce41a7bea9bce3c95b634c03cb6b1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _transformer_encoder_layer_fwd_out(at::Tensor & out, const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask={}, ::std::optional mask_type=::std::nullopt); +TORCH_API at::Tensor & _transformer_encoder_layer_fwd_outf(const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask, ::std::optional mask_type, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c6ad5ae5d3611dbee441d2ea87a0505519f6a82a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _trilinear_out(at::Tensor & out, const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim=1); +TORCH_API at::Tensor & _trilinear_outf(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c3e2b72c693e16fc580e9ea9126891378255d3df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _trilinear { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_trilinear"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_trilinear(Tensor i1, Tensor i2, Tensor i3, int[] expand1, int[] expand2, int[] expand3, int[] sumdim, int unroll_dim=1) -> Tensor"; + static at::Tensor call(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim); +}; + +struct TORCH_API _trilinear_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_trilinear"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_trilinear.out(Tensor i1, Tensor i2, Tensor i3, int[] expand1, int[] expand2, int[] expand3, int[] sumdim, int unroll_dim=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention.h new file mode 100644 index 0000000000000000000000000000000000000000..30a73856ac56d843aa5ba6d74836c61191f287b2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_triton_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None) -> Tensor +inline at::Tensor _triton_multi_head_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}) { + return at::_ops::_triton_multi_head_attention::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask); +} + +// aten::_triton_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _triton_multi_head_attention_out(at::Tensor & out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}) { + return at::_ops::_triton_multi_head_attention_out::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, out); +} +// aten::_triton_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _triton_multi_head_attention_outf(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, at::Tensor & out) { + return at::_ops::_triton_multi_head_attention_out::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8b391606e14b63e45ae7ba65f5354615ee30e63e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _triton_multi_head_attention_out(at::Tensor & out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}); +TORCH_API at::Tensor & _triton_multi_head_attention_outf(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3499dc11a2d8d964219f3fe1a2f4a922215520b8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_multi_head_attention_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _triton_multi_head_attention { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_triton_multi_head_attention"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_triton_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None) -> Tensor"; + static at::Tensor call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask); +}; + +struct TORCH_API _triton_multi_head_attention_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_triton_multi_head_attention"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_triton_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8af14d73c569b0cba19c8d49f694ab8c068fff3b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _triton_scaled_dot_attention { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_triton_scaled_dot_attention"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor"; + static at::Tensor call(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p); +}; + +struct TORCH_API _triton_scaled_dot_attention_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_triton_scaled_dot_attention"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index.h new file mode 100644 index 0000000000000000000000000000000000000000..a5504017b23a6f96dc0f4c01abf4daae5434feb8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_unsafe_index.Tensor(Tensor self, Tensor?[] indices) -> Tensor +inline at::Tensor _unsafe_index(const at::Tensor & self, const c10::List<::std::optional> & indices) { + return at::_ops::_unsafe_index_Tensor::call(self, indices); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1bbd9aca34dcf1f0022b2e5ab15bd15a43da7df8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _unsafe_index(const at::Tensor & self, const c10::List<::std::optional> & indices); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_view_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_view_native.h new file mode 100644 index 0000000000000000000000000000000000000000..54fa9c0c6640094d07dbd261e260f0efef9e6730 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_view_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _unsafe_view(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor & _unsafe_view_out_symint(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f96a7aede473fd1295f4d444305a97f8694ec0c7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _upsample_bicubic2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_bicubic2d_aa_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb4a0a82320930ccd63b3b0a20dbcaaf97cd6250 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _upsample_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f19b1374d854ef82f45dcc607ddc88eaa05d0bc3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _upsample_bicubic2d_aa_vec { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional>); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_upsample_bicubic2d_aa"; + static constexpr const char* overload_name = "vec"; + static constexpr const char* schema_str = "_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor"; + static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +}; + +struct TORCH_API _upsample_bicubic2d_aa_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_upsample_bicubic2d_aa"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +}; + +struct TORCH_API _upsample_bicubic2d_aa { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_upsample_bicubic2d_aa"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa.h new file mode 100644 index 0000000000000000000000000000000000000000..906406c21e7328a80a59233a9c2fba57e86899be --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa.h @@ -0,0 +1,119 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bilinear2d_aa_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor _upsample_bilinear2d_aa(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bilinear2d_aa_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); + } +} + +// aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bilinear2d_aa_vec::call(input, output_size, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor _upsample_bilinear2d_aa(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bilinear2d_aa_vec::call(input, output_size, align_corners, scale_factors); + } +} + +// aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bilinear2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bilinear2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bilinear2d_aa_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bilinear2d_aa_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bilinear2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bilinear2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor _upsample_bilinear2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w); + } +} + +// aten::_upsample_bilinear2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa::call(self, output_size, align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor _upsample_bilinear2d_aa(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa::call(self, output_size, align_corners, scales_h, scales_w); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..42692c27e1760db2d5f46748bdda1e5429064ed9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_bilinear2d_aa_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_native.h new file mode 100644 index 0000000000000000000000000000000000000000..90f6703c5723bc188330162980338d8bcb299bdf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_native.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +TORCH_API at::Tensor _upsample_bilinear2d_aa(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +struct TORCH_API structured__upsample_bilinear2d_aa_out_cpu : public at::meta::structured__upsample_bilinear2d_aa { +void impl(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +struct TORCH_API structured__upsample_bilinear2d_aa_out_cuda : public at::meta::structured__upsample_bilinear2d_aa { +void impl(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..81e923248d33cd2cbfe77c38371350cdbeb7185a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _upsample_nearest_exact1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..14bed88067c2d59506ed448f40a3e2940c29aa57 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out); +TORCH_API at::Tensor & _upsample_nearest_exact1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0ea889ebaafdd4cf7c684445907249b1dabb41bf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured__upsample_nearest_exact2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7726d2920f4f7601c767c6daefdad3464ef2c980 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _upsample_nearest_exact2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +TORCH_API at::Tensor _upsample_nearest_exact2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0c3bf8234734e728d7c8885c5c59954cc8c73edc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured__upsample_nearest_exact3d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1098ba4118de870d0b08a8859508fa9192dc4550 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _upsample_nearest_exact3d_vec { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, ::std::optional>); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_upsample_nearest_exact3d"; + static constexpr const char* overload_name = "vec"; + static constexpr const char* schema_str = "_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor"; + static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); +}; + +struct TORCH_API _upsample_nearest_exact3d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_upsample_nearest_exact3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_upsample_nearest_exact3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +}; + +struct TORCH_API _upsample_nearest_exact3d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_upsample_nearest_exact3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_upsample_nearest_exact3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0df9c28a901d2c6ec246de742ca22f194e056db4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank); +TORCH_API bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..260cda5b393228747f7917eedae146e1fd6324c3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _use_cudnn_rnn_flatten_weight { + using schema = bool (); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_use_cudnn_rnn_flatten_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_use_cudnn_rnn_flatten_weight() -> bool"; + static bool call(); + static bool redispatch(c10::DispatchKeySet dispatchKeySet); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_compressed_sparse_indices_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_compressed_sparse_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7683e53be3883c8533b06274121920e6da802a1a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_compressed_sparse_indices_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _validate_compressed_sparse_indices { + using schema = void (bool, const at::Tensor &, const at::Tensor &, int64_t, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_validate_compressed_sparse_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_validate_compressed_sparse_indices(bool is_crow, Tensor compressed_idx, Tensor plain_idx, int cdim, int dim, int nnz) -> ()"; + static void call(bool is_crow, const at::Tensor & compressed_idx, const at::Tensor & plain_idx, int64_t cdim, int64_t dim, int64_t nnz); + static void redispatch(c10::DispatchKeySet dispatchKeySet, bool is_crow, const at::Tensor & compressed_idx, const at::Tensor & plain_idx, int64_t cdim, int64_t dim, int64_t nnz); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a4e6a0cffe869884aab134b926cd5fe238bd5c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API void _validate_sparse_bsc_tensor_args(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional check_pinning=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_native.h new file mode 100644 index 0000000000000000000000000000000000000000..606de004ec901660feda07d562092f353099fc06 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void _validate_sparse_bsc_tensor_args(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional check_pinning=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args.h new file mode 100644 index 0000000000000000000000000000000000000000..70f77cedd451bc6f7f1404200480c63d1d939d8d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_validate_sparse_csc_tensor_args(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, bool? check_pinning=None) -> () +inline void _validate_sparse_csc_tensor_args(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional check_pinning=::std::nullopt) { + return at::_ops::_validate_sparse_csc_tensor_args::call(ccol_indices, row_indices, values, size, check_pinning); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_values_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_values_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c438813e17f89a7944904815e139ba3a5db77dce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_values_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _values_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & _values_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d8f9ad7615414aefb619c4464a55712292b7a4a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _weight_int4pack_mm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_weight_int4pack_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_weight_int4pack_mm(Tensor self, Tensor mat2, int qGroupSize, Tensor qScaleAndZeros) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..28538f7f71713018738c6e5399d8c3068faa85d8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _weight_int8pack_mm(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scales); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..0a1948f58135ed21c6ff7d8418f94e25dc3473ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_weight_norm(Tensor v, Tensor g, int dim=0) -> Tensor +inline at::Tensor _weight_norm(const at::Tensor & v, const at::Tensor & g, int64_t dim=0) { + return at::_ops::_weight_norm::call(v, g, dim); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cbc189450438d8ded976143386c9d8bd87ffd971 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _weight_norm(const at::Tensor & v, const at::Tensor & g, int64_t dim=0); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_differentiable_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_differentiable_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80c20274501316f1a1c1762296675480bae21d8d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_differentiable_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _weight_norm_differentiable_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_weight_norm_differentiable_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_weight_norm_differentiable_backward(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface.h new file mode 100644 index 0000000000000000000000000000000000000000..7284e36e5f93285f62881b41772cd9b08133c752 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor) +inline ::std::tuple _weight_norm_interface(const at::Tensor & v, const at::Tensor & g, int64_t dim=0) { + return at::_ops::_weight_norm_interface::call(v, g, dim); +} + +// aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _weight_norm_interface_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & v, const at::Tensor & g, int64_t dim=0) { + return at::_ops::_weight_norm_interface_out::call(v, g, dim, out0, out1); +} +// aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _weight_norm_interface_outf(const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_weight_norm_interface_out::call(v, g, dim, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_wrapped_quantized_linear_prepacked_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_wrapped_quantized_linear_prepacked_native.h new file mode 100644 index 0000000000000000000000000000000000000000..67df932bc5197c7a559fe76a81de8fbc0a80e2e0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_wrapped_quantized_linear_prepacked_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _wrapped_quantized_linear_prepacked(const at::Tensor & input, const at::Tensor & input_scale, const at::Tensor & input_zero_point, const at::Tensor & packed_weight, const at::Tensor & output_scale, const at::Tensor & output_zero_point, int64_t out_channel); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e20a5ba9353b8cafe3ba9acd2953c590ce8fd49e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor acos(const at::Tensor & self); +TORCH_API at::Tensor & acos_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & acos_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & acos_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acosh_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acosh_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3e667e60844aa36b80a8ca2dbd4ae3b97b1b4e3a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acosh_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor acosh(const at::Tensor & self); +TORCH_API at::Tensor & acosh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & acosh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & acosh_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..962c6389d9713d4a06b5ab245dc339848a2ff4e1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API adaptive_avg_pool1d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::adaptive_avg_pool1d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +struct TORCH_API adaptive_avg_pool1d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::adaptive_avg_pool1d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "adaptive_avg_pool1d.out(Tensor self, int[1] output_size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1796f327153b06e3ec18461f17506134182a963e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor adaptive_avg_pool3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool1d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool1d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5db31ae08407d9f9f18f3d063e18e0c56bfd9a94 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool1d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple adaptive_max_pool1d(const at::Tensor & self, at::IntArrayRef output_size); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f0708fcecff8c057a99b5ef6c3179b1739028c29 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_adaptive_max_pool2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::IntArrayRef output_size); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4690ee63b974f2ef0ae1df5ac23781b4758d7ab4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple adaptive_max_pool2d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool2d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b60c519805591b222072df3ddc04e9d4d0e21bcd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API adaptive_max_pool2d_out { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::adaptive_max_pool2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "adaptive_max_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); +}; + +struct TORCH_API adaptive_max_pool2d { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::adaptive_max_pool2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "adaptive_max_pool2d(Tensor self, int[2] output_size) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..da539f96f4dbc4d4785a8b256b2ec233feffdaa1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::adaptive_max_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple adaptive_max_pool3d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_max_pool3d_out::call(self, output_size, out, indices); +} +// aten::adaptive_max_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple adaptive_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices) { + return at::_ops::adaptive_max_pool3d_out::call(self, output_size, out, indices); +} + +// aten::adaptive_max_pool3d(Tensor self, int[3] output_size) -> (Tensor, Tensor) +inline ::std::tuple adaptive_max_pool3d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_max_pool3d::call(self, output_size); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a45cff56658a4e61357fd0b9930d3fbb86a39cff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor adaptive_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b4b7238d3f172499694ef027aa6a7b61ec0dfa46 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API adaptive_max_pool3d_out { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::adaptive_max_pool3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "adaptive_max_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); +}; + +struct TORCH_API adaptive_max_pool3d { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::adaptive_max_pool3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "adaptive_max_pool3d(Tensor self, int[3] output_size) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv.h new file mode 100644 index 0000000000000000000000000000000000000000..332e9284731804c6e80dfca8275a72ada7bd5d1f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addcdiv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1) { + return at::_ops::addcdiv_out::call(self, tensor1, tensor2, value, out); +} +// aten::addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addcdiv_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out) { + return at::_ops::addcdiv_out::call(self, tensor1, tensor2, value, out); +} + +// aten::addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor +inline at::Tensor addcdiv(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1) { + return at::_ops::addcdiv::call(self, tensor1, tensor2, value); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c6fb2cce5ce764b7e9d00ae8a41df348f792ad4b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_addcdiv_out : public at::meta::structured_addcdiv { +void impl(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1838761a1a775391cdce74afc09a85fdc461a36e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API addcdiv_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addcdiv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +}; + +struct TORCH_API addcdiv { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addcdiv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +struct TORCH_API addcdiv_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addcdiv_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addcdiv_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmv_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c56ab77c8c1cf46119d754864b23007477a99fec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmv_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API addmv { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addmv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addmv(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API addmv_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addmv_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addmv_(Tensor(a!) self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API addmv_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addmv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "addmv.out(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addr.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addr.h new file mode 100644 index 0000000000000000000000000000000000000000..83fe939778bff6fd697eccd4f812b471d7a772fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addr.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::addr(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addr::call(self, vec1, vec2, beta, alpha); +} + +// aten::addr.out(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addr_out::call(self, vec1, vec2, beta, alpha, out); +} +// aten::addr.out(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addr_outf(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::addr_out::call(self, vec1, vec2, beta, alpha, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adjoint_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adjoint_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f16b41dc4d0050acd9f51771585cf21af607e771 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adjoint_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor adjoint(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alias_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alias_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9a3b2a26292e4c9e90801386a5422b00147b527 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alias_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & alias_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & alias_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors.h new file mode 100644 index 0000000000000000000000000000000000000000..bdfeaae63201db89c45e052362ff367d93587717 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::align_tensors(Tensor[] tensors) -> Tensor[] +inline ::std::vector align_tensors(at::TensorList tensors) { + return at::_ops::align_tensors::call(tensors); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b5610c2326af0a34477e07732804de6e3607b8a2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API align_tensors { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::align_tensors"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "align_tensors(Tensor[] tensors) -> Tensor[]"; + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amax_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amax_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a543d67c35996a005496c4715b51d4d5d4b48286 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amax_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor amax(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amin_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amin_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d886b4623dc1f26d75b25d9fe4cc633619d0f58f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amin_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_amin : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::IntArrayRef dim, bool keepdim); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34d4ea3cf010cbd2eac8082e7bb34ab07c4f90dc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple aminmax(const at::Tensor & self, ::std::optional dim=::std::nullopt, bool keepdim=false); +TORCH_API ::std::tuple aminmax_out(at::Tensor & min, at::Tensor & max, const at::Tensor & self, ::std::optional dim=::std::nullopt, bool keepdim=false); +TORCH_API ::std::tuple aminmax_outf(const at::Tensor & self, ::std::optional dim, bool keepdim, at::Tensor & min, at::Tensor & max); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8c77d4f1536010f65084e58d3fbdec92f7cefb24 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API aminmax { + using schema = ::std::tuple (const at::Tensor &, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::aminmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max)"; + static ::std::tuple call(const at::Tensor & self, ::std::optional dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim, bool keepdim); +}; + +struct TORCH_API aminmax_out { + using schema = ::std::tuple (const at::Tensor &, ::std::optional, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::aminmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max)"; + static ::std::tuple call(const at::Tensor & self, ::std::optional dim, bool keepdim, at::Tensor & min, at::Tensor & max); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim, bool keepdim, at::Tensor & min, at::Tensor & max); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/and_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/and_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..32eb545e4e6b5069cd93a1b034968114c3cd0cc7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/and_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API __and___Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__and__"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "__and__.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API __and___Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__and__"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "__and__.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API __iand___Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__iand__"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "__iand__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API __iand___Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__iand__"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "__iand__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any.h new file mode 100644 index 0000000000000000000000000000000000000000..23c1927e7036765249e2fea201f8b36d0529aab4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any.h @@ -0,0 +1,87 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor +inline at::Tensor any(const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::any_dim::call(self, dim, keepdim); +} + +// aten::any.dims(Tensor self, int[]? dim=None, bool keepdim=False) -> Tensor +inline at::Tensor any(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false) { + return at::_ops::any_dims::call(self, dim, keepdim); +} + +// aten::any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::any_out::call(self, dim, keepdim, out); +} +// aten::any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out) { + return at::_ops::any_out::call(self, dim, keepdim, out); +} + +// aten::any.dims_out(Tensor self, int[]? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false) { + return at::_ops::any_dims_out::call(self, dim, keepdim, out); +} +// aten::any.dims_out(Tensor self, int[]? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out) { + return at::_ops::any_dims_out::call(self, dim, keepdim, out); +} + +// aten::any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor +inline at::Tensor any(const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::any_dimname::call(self, dim, keepdim); +} + +// aten::any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::any_dimname_out::call(self, dim, keepdim, out); +} +// aten::any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out) { + return at::_ops::any_dimname_out::call(self, dim, keepdim, out); +} + +// aten::any(Tensor self) -> Tensor +inline at::Tensor any(const at::Tensor & self) { + return at::_ops::any::call(self); +} + +// aten::any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::any_all_out::call(self, out); +} +// aten::any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & any_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::any_all_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..77906ec66e263f04afa73c7af7855fbd45cefbdb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_cpu_dispatch.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor any(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor any(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor any(const at::Tensor & self); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d703e2cfbfd147927720af544221058baf10f0fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_ops.h @@ -0,0 +1,111 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API any_dim { + using schema = at::Tensor (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim); +}; + +struct TORCH_API any_dims { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "dims"; + static constexpr const char* schema_str = "any.dims(Tensor self, int[]? dim=None, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim); +}; + +struct TORCH_API any_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API any_dims_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "dims_out"; + static constexpr const char* schema_str = "any.dims_out(Tensor self, int[]? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API any_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim); +}; + +struct TORCH_API any_dimname_out { + using schema = at::Tensor & (const at::Tensor &, at::Dimname, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "dimname_out"; + static constexpr const char* schema_str = "any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API any { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "any(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API any_all_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::any"; + static constexpr const char* overload_name = "all_out"; + static constexpr const char* schema_str = "any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d33ddeaa945827093065154177f42a5845fab4d0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_meta_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & arange_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step); +TORCH_API at::Tensor & arange_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b51495085cb5207bae6c6a13ce88fe28b109041d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_ops.h @@ -0,0 +1,78 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API arange { + using schema = at::Tensor (const at::Scalar &, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::arange"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "arange(Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API arange_start { + using schema = at::Tensor (const at::Scalar &, const at::Scalar &, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::arange"; + static constexpr const char* overload_name = "start"; + static constexpr const char* schema_str = "arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API arange_start_step { + using schema = at::Tensor (const at::Scalar &, const at::Scalar &, const at::Scalar &, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::arange"; + static constexpr const char* overload_name = "start_step"; + static constexpr const char* schema_str = "arange.start_step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API arange_out { + using schema = at::Tensor & (const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::arange"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "arange.out(Scalar end, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & end, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & end, at::Tensor & out); +}; + +struct TORCH_API arange_start_out { + using schema = at::Tensor & (const at::Scalar &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::arange"; + static constexpr const char* overload_name = "start_out"; + static constexpr const char* schema_str = "arange.start_out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arcsinh_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arcsinh_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..137da143773699330c35ef818857487ed9f078bf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arcsinh_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor arcsinh(const at::Tensor & self); +TORCH_API at::Tensor & arcsinh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & arcsinh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & arcsinh_(at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmax_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmax_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..92e0211bd84a9523d11d8710556056e8d0ae556f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmax_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor argmax(const at::Tensor & self, ::std::optional dim=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & argmax_out(at::Tensor & out, const at::Tensor & self, ::std::optional dim=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & argmax_outf(const at::Tensor & self, ::std::optional dim, bool keepdim, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmin_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..deabe1cdf272838f4f3f1bf45c1d289964bd16f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmin_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_argmin_out : public at::meta::structured_argmin { +void impl(const at::Tensor & self, ::std::optional dim, bool keepdim, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2d2076519cf14c0107a7357ef4e5b03ff2f04032 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor as_strided_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt); +TORCH_API at::Tensor as_strided_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c877e57aa06a225dc73910db8d2ac3c420bee8e3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API as_strided_copy { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::as_strided_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "as_strided_copy(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset); +}; + +struct TORCH_API as_strided_copy_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::as_strided_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..385548cee575a07cecbca49545a9852166ec39c6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor as_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt); +TORCH_API at::Tensor as_strided_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8462ab7c0c14a699e71f99290fd5e53d7720a229 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor atan(const at::Tensor & self); +TORCH_API at::Tensor & atan_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c376bcb2fff01a905a0382b9005371ad9f993836 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor atan(const at::Tensor & self); +TORCH_API at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atan_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3614f1741e853e8825172577c3981fe7d017fc28 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor atan(const at::Tensor & self); +TORCH_API at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atan_(at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bb2e886c2fff5b79f7169170b38e50bbef0e5180 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor atanh(const at::Tensor & self); +TORCH_API at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atanh_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d.h new file mode 100644 index 0000000000000000000000000000000000000000..13cbb7e625b141c6caf26072f55ed967359e6c4a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::atleast_3d(Tensor self) -> Tensor +inline at::Tensor atleast_3d(const at::Tensor & self) { + return at::_ops::atleast_3d::call(self); +} + +// aten::atleast_3d.Sequence(Tensor[] tensors) -> Tensor[] +inline ::std::vector atleast_3d(at::TensorList tensors) { + return at::_ops::atleast_3d_Sequence::call(tensors); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9336475ca68a0798779ac558e3fa01cccf4ce01d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor atleast_3d(const at::Tensor & self); +TORCH_API ::std::vector atleast_3d(at::TensorList tensors); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool1d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..da53ab8c9c4bbf3c17af663b7dca05550c0508f9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool1d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API avg_pool1d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::avg_pool1d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad); +}; + +struct TORCH_API avg_pool1d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::avg_pool1d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "avg_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..e0d17657ba5d3f84d66d8845f8a56e621b2575bf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::avg_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & avg_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override) { + return at::_ops::avg_pool2d_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); +} +// aten::avg_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input) { + return at::_ops::avg_pool2d_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); +} + +// aten::avg_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor +inline at::Tensor avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override) { + return at::_ops::avg_pool2d_backward::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7006692c81da7f3124951ba3ad1526ac0be59ae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b9a3043a0c1c46d41c23e82b1f1916d132156eb6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e4e67ea2d47e0e55fc268455465298d5f3938b45 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_avg_pool2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..59ac86eacefe258c0ca8c6a9047e7286360b2cb4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, ::std::optional divisor_override=::std::nullopt) { + return at::_ops::avg_pool3d_out::call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); +} +// aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & out) { + return at::_ops::avg_pool3d_out::call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); +} + +// aten::avg_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor +inline at::Tensor avg_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, ::std::optional divisor_override=::std::nullopt) { + return at::_ops::avg_pool3d::call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b8c2f2a00b703ab1c6dc1c8117b795db3bcc8afb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c832fdf6e36ce896fe32ad4dbff9e124a216b5cd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8ded80ff6120fc91983f3aef24a701506de592db --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_avg_pool3d_backward_out_cpu : public at::meta::structured_avg_pool3d_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, const at::Tensor & grad_input); +}; +struct TORCH_API structured_avg_pool3d_backward_out_cuda : public at::meta::structured_avg_pool3d_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, const at::Tensor & grad_input); +}; +TORCH_API at::Tensor mkldnn_avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & mkldnn_avg_pool3d_backward_out(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bartlett_window_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bartlett_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5a5ebac4c52f2f6389deb200d88bfbca27c5d5d8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bartlett_window_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor bartlett_window(int64_t window_length, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & bartlett_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor bartlett_window(int64_t window_length, bool periodic, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & bartlett_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..c200005888d5365049100870fbdc17aa0acd2490 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::batch_norm_backward(Tensor grad_out, Tensor input, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, bool update, float eps, bool[3] output_mask, Tensor reserve) -> (Tensor, Tensor, Tensor) +inline ::std::tuple batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, bool update, double eps, ::std::array output_mask, const at::Tensor & reserve) { + return at::_ops::batch_norm_backward::call(grad_out, input, weight, running_mean, running_var, save_mean, save_var, update, eps, output_mask, reserve); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c9fc10a9b1f0a0937b6752e0da61d398d4e91858 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API batch_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, ::std::array, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "batch_norm_backward(Tensor grad_out, Tensor input, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, bool update, float eps, bool[3] output_mask, Tensor reserve) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, bool update, double eps, ::std::array output_mask, const at::Tensor & reserve); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, bool update, double eps, ::std::array output_mask, const at::Tensor & reserve); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8acd0814596a576a99f88b3f8b507a51454de4c7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple batch_norm_backward_reduce(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7d033f2c278c3fe5d27271143aa060ee0b498add --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple batch_norm_backward_reduce_out(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple batch_norm_backward_reduce_cuda(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ea33b5311236cb22faacbde258ff9291a1155d8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple batch_norm_gather_stats_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, int64_t count); +TORCH_API ::std::tuple batch_norm_gather_stats_outf(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, int64_t count, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6104f66b13819fb77a837d2da08769e3e2629918 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple batch_norm_gather_stats_with_counts_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, const at::Tensor & counts); +TORCH_API ::std::tuple batch_norm_gather_stats_with_counts_outf(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, const at::Tensor & counts, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..967f7d19cb35a095097339cd7482923587097409 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple batch_norm_gather_stats_with_counts(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, const at::Tensor & counts); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_stats_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_stats_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5a3907b8cdddc185a054a5484dffc6343cd82053 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_stats_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple batch_norm_stats(const at::Tensor & input, double eps); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_stats_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_stats_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c16f498342bbe72dc07515c90e0577835fb1d515 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_stats_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple batch_norm_stats_out(const at::Tensor & input, double eps, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple batch_norm_stats_cuda(const at::Tensor & input, double eps); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a7ad8fa9041e8ce6249f68ca489859005dceed7e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor bernoulli(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b15c83074c18cc09c2651cdd21bbd74be41a58e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & bernoulli_out(at::Tensor & out, const at::Tensor & self, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & bernoulli_outf(const at::Tensor & self, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & bernoulli_(at::Tensor & self, const at::Tensor & p, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & bernoulli_(at::Tensor & self, double p=0.5, ::std::optional generator=::std::nullopt); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bilinear_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bilinear_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..74ae89c9c069d95f8eaa4ca40900738aeb446896 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bilinear_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bilinear { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bilinear"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "bilinear(Tensor input1, Tensor input2, Tensor weight, Tensor? bias=None) -> Tensor"; + static at::Tensor call(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const ::std::optional & bias); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const ::std::optional & bias); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9321ded5c3b72d9373b12204d66da8b4f9cfcc80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor binary_cross_entropy(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & binary_cross_entropy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & binary_cross_entropy_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9449866154194ea18fd58e5cfa4a1c9f1eb9ecef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API binary_cross_entropy { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::binary_cross_entropy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "binary_cross_entropy(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction); +}; + +struct TORCH_API binary_cross_entropy_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::binary_cross_entropy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "binary_cross_entropy.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..10838a82dbb099b0e08e3fcd46afd698b405b1c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bincount(const at::Tensor & self, const ::std::optional & weights={}, int64_t minlength=0); +TORCH_API at::Tensor bincount_symint(const at::Tensor & self, const ::std::optional & weights={}, c10::SymInt minlength=0); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_native.h new file mode 100644 index 0000000000000000000000000000000000000000..40ad83297e37083becf91ca0e5ca6af67f195076 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & bincount_out_symint(const at::Tensor & self, const ::std::optional & weights, c10::SymInt minlength, at::Tensor & out); +TORCH_API at::Tensor _bincount_cpu(const at::Tensor & self, const ::std::optional & weights={}, int64_t minlength=0); +TORCH_API at::Tensor _bincount_cuda(const at::Tensor & self, const ::std::optional & weights={}, int64_t minlength=0); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binomial_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binomial_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..af7cdaa4e9c77ee939ccf642e4d1270b1003fee3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binomial_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API binomial { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::binomial"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & count, const at::Tensor & prob, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & count, const at::Tensor & prob, ::std::optional generator); +}; + +struct TORCH_API binomial_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::binomial"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & count, const at::Tensor & prob, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & count, const at::Tensor & prob, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b2dbebde40e68a7c2a03348d2d1dc67fb3ac01d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not.h new file mode 100644 index 0000000000000000000000000000000000000000..0bcca131e0631aca21bb0c2d6648e9764cad7047 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::bitwise_not(Tensor self) -> Tensor +inline at::Tensor bitwise_not(const at::Tensor & self) { + return at::_ops::bitwise_not::call(self); +} + +// aten::bitwise_not.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::bitwise_not_out::call(self, out); +} +// aten::bitwise_not.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::bitwise_not_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not_native.h new file mode 100644 index 0000000000000000000000000000000000000000..97c7004831c2fcfad46ae023248553f4fdc51653 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_bitwise_not_out : public at::meta::structured_bitwise_not { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or.h new file mode 100644 index 0000000000000000000000000000000000000000..92a00d968d26a39e66cdc1a6282b779484f331db --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::bitwise_or.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_or_Tensor_out::call(self, other, out); +} +// aten::bitwise_or.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_or_Tensor_out::call(self, other, out); +} + +// aten::bitwise_or.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_or_Scalar_out::call(self, other, out); +} +// aten::bitwise_or.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::bitwise_or_Scalar_out::call(self, other, out); +} + +// aten::bitwise_or.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor bitwise_or(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_or_Scalar::call(self, other); +} + +// aten::bitwise_or.Scalar_Tensor(Scalar self, Tensor other) -> Tensor +inline at::Tensor bitwise_or(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_or_Scalar_Tensor::call(self, other); +} + +// aten::bitwise_or.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor bitwise_or(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_or_Tensor::call(self, other); +} + +// aten::bitwise_or.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_or_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_or_Scalar_Tensor_out::call(self, other, out); +} +// aten::bitwise_or.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_or_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_or_Scalar_Tensor_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..347f061f72a2a8792da51f7240140859740c743f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_compositeexplicitautograd_dispatch.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor bitwise_or(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_or_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor bitwise_or(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44d0decfdf12b78d057ac2f09f9397c45448b5e0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor bitwise_or(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_or_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ffac5f6ffb9e36ad9bcfcc268ff26758026c33cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_bitwise_or_out : public at::meta::structured_bitwise_or_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor bitwise_or(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_or_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_or_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor bitwise_or(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_Scalar_Tensor_out(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift.h new file mode 100644 index 0000000000000000000000000000000000000000..09f6b3097b5be958fc0f686676457b9c6d3a9ac9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::bitwise_right_shift.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Tensor::call(self, other); +} + +// aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Tensor_out::call(self, other, out); +} +// aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_right_shift_Tensor_out::call(self, other, out); +} + +// aten::bitwise_right_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_right_shift_Tensor_Scalar::call(self, other); +} + +// aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_right_shift_Tensor_Scalar_out::call(self, other, out); +} +// aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::bitwise_right_shift_Tensor_Scalar_out::call(self, other, out); +} + +// aten::bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor +inline at::Tensor bitwise_right_shift(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Scalar_Tensor::call(self, other); +} + +// aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Scalar_Tensor_out::call(self, other, out); +} +// aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_right_shift_Scalar_Tensor_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/block_diag_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/block_diag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fcb57216b3284bf07efcef2123900690a58b5d3e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/block_diag_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API block_diag { + using schema = at::Tensor (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::block_diag"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "block_diag(Tensor[] tensors) -> Tensor"; + static at::Tensor call(at::TensorList tensors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +struct TORCH_API block_diag_out { + using schema = at::Tensor & (at::TensorList, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::block_diag"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "block_diag.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::TensorList tensors, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..76877e157785c28eb3e64a6ed9d2098c674dc817 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bmm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4990e1c7c986796d7b783064127bc840fa26631 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bmm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bmm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "bmm(Tensor self, Tensor mat2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2); +}; + +struct TORCH_API bmm_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bmm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "bmm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +}; + +struct TORCH_API bmm_dtype { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bmm"; + static constexpr const char* overload_name = "dtype"; + static constexpr const char* schema_str = "bmm.dtype(Tensor self, Tensor mat2, ScalarType out_dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +}; + +struct TORCH_API bmm_dtype_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bmm"; + static constexpr const char* overload_name = "dtype_out"; + static constexpr const char* schema_str = "bmm.dtype_out(Tensor self, Tensor mat2, ScalarType out_dtype, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_to_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_to_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3cc210048092d4a182140d2451fd7c961b2dd49d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_to_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API broadcast_to { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::broadcast_to"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bucketize_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bucketize_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b40af6335d5ad258d9e808278d8534035ea4265a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bucketize_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bucketize(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); +TORCH_API at::Tensor & bucketize_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); +TORCH_API at::Tensor & bucketize_outf(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); +TORCH_API at::Tensor bucketize(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bucketize_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bucketize_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5e524457020185d4368ab4e522e25dc585668f02 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bucketize_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bucketize_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bucketize"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right); +}; + +struct TORCH_API bucketize_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bucketize"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "bucketize.Tensor_out(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); +}; + +struct TORCH_API bucketize_Scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bucketize"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "bucketize.Scalar(Scalar self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32, bool right); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & boundaries, bool out_int32, bool right); +}; + +struct TORCH_API bucketize_Scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::bucketize"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "bucketize.Scalar_out(Scalar self, Tensor boundaries, *, bool out_int32=False, bool right=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c7d084ef6523ef8225d2243ed3a3e9dcced80065 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor cartesian_prod(at::TensorList tensors); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cat_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cat_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e98e7cd13fb3865e30ec65acee2a015fa18155e7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cat_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor cat(at::TensorList tensors, at::Dimname dim); +TORCH_API at::Tensor & cat_out(at::Tensor & out, at::TensorList tensors, at::Dimname dim); +TORCH_API at::Tensor & cat_outf(at::TensorList tensors, at::Dimname dim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cat_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cat_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5203ee667257ef68763d1c6ffd2f3f7f737bf9d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cat_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cat { + using schema = at::Tensor (const at::ITensorListRef &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cat"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cat(Tensor[] tensors, int dim=0) -> Tensor"; + static at::Tensor call(const at::ITensorListRef & tensors, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::ITensorListRef & tensors, int64_t dim); +}; + +struct TORCH_API cat_out { + using schema = at::Tensor & (const at::ITensorListRef &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cat"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out); +}; + +struct TORCH_API cat_names { + using schema = at::Tensor (at::TensorList, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cat"; + static constexpr const char* overload_name = "names"; + static constexpr const char* schema_str = "cat.names(Tensor[] tensors, Dimname dim) -> Tensor"; + static at::Tensor call(at::TensorList tensors, at::Dimname dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Dimname dim); +}; + +struct TORCH_API cat_names_out { + using schema = at::Tensor & (at::TensorList, at::Dimname, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cat"; + static constexpr const char* overload_name = "names_out"; + static constexpr const char* schema_str = "cat.names_out(Tensor[] tensors, Dimname dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::TensorList tensors, at::Dimname dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Dimname dim, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91314c81d2faaf43b2a18054b9b65d37e7ff9884 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & cauchy_(at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4a9b1177351ed1ea068d09ee1f4b5f69e31d585c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cauchy_ { + using schema = at::Tensor & (at::Tensor &, double, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cauchy_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cauchy_(Tensor(a!) self, float median=0, float sigma=1, *, Generator? generator=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, double median, double sigma, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double median, double sigma, ::std::optional generator); +}; + +struct TORCH_API cauchy_out { + using schema = at::Tensor & (const at::Tensor &, double, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cauchy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cauchy.out(Tensor self, float median=0, float sigma=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double median, double sigma, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double median, double sigma, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API cauchy { + using schema = at::Tensor (const at::Tensor &, double, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cauchy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cauchy(Tensor self, float median=0, float sigma=1, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, double median, double sigma, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double median, double sigma, ::std::optional generator); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5f50b11858ae9b250220560f392e9227a373b0c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor ccol_indices_default(const at::Tensor & self); +TORCH_API at::Tensor ccol_indices_sparse_csr(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cdist_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cdist_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5978b2a4fe0cafe2098e53967ffa37552c8acab4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cdist_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cdist { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cdist"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cdist(Tensor x1, Tensor x2, float p=2, int? compute_mode=None) -> Tensor"; + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ceil_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ceil_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..75fccb6252a558388dbd07148877b7a1b11f50b2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ceil_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor ceil(const at::Tensor & self); +TORCH_API at::Tensor & ceil_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ceil_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ceil_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d3ada1869b9454b2797a52dcf15d5d4ae65dcf3e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ceil_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API ceil { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::ceil"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ceil(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API ceil_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::ceil_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ceil_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API ceil_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::ceil"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "ceil.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/celu_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/celu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..67a5a717555db36e0995d780ea4deb00d481c2fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/celu_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor celu(const at::Tensor & self, const at::Scalar & alpha=1.0); +TORCH_API at::Tensor & celu_out(const at::Tensor & self, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & celu_(at::Tensor & self, const at::Scalar & alpha=1.0); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/celu_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/celu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1b409e1e21b71174824ddd9012aa27a6894f9add --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/celu_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API celu { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::celu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "celu(Tensor self, Scalar alpha=1.0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & alpha); +}; + +struct TORCH_API celu_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::celu_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "celu_(Tensor(a!) self, Scalar alpha=1.0) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & alpha); +}; + +struct TORCH_API celu_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::celu"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "celu.out(Tensor self, Scalar alpha=1.0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/chain_matmul.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/chain_matmul.h new file mode 100644 index 0000000000000000000000000000000000000000..19b5c9f3cdf89a75648d43b8b77c3eb4cf1c4026 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/chain_matmul.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::chain_matmul(Tensor[] matrices) -> Tensor +inline at::Tensor chain_matmul(at::TensorList matrices) { + return at::_ops::chain_matmul::call(matrices); +} + +// aten::chain_matmul.out(Tensor[] matrices, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & chain_matmul_out(at::Tensor & out, at::TensorList matrices) { + return at::_ops::chain_matmul_out::call(matrices, out); +} +// aten::chain_matmul.out(Tensor[] matrices, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & chain_matmul_outf(at::TensorList matrices, at::Tensor & out) { + return at::_ops::chain_matmul_out::call(matrices, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c45bda557cde5f291049471e2dcfa874a0de924 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky.h new file mode 100644 index 0000000000000000000000000000000000000000..9ea4afe698bb7ea17bdeaaed655ac9dd6e558f93 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cholesky_out(at::Tensor & out, const at::Tensor & self, bool upper=false) { + return at::_ops::cholesky_out::call(self, upper, out); +} +// aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cholesky_outf(const at::Tensor & self, bool upper, at::Tensor & out) { + return at::_ops::cholesky_out::call(self, upper, out); +} + +// aten::cholesky(Tensor self, bool upper=False) -> Tensor +inline at::Tensor cholesky(const at::Tensor & self, bool upper=false) { + return at::_ops::cholesky::call(self, upper); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_solve.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_solve.h new file mode 100644 index 0000000000000000000000000000000000000000..1410810eb639c3e5c1d79b51fdb7b3bf2f3a0a58 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_solve.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cholesky_solve.out(Tensor self, Tensor input2, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cholesky_solve_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & input2, bool upper=false) { + return at::_ops::cholesky_solve_out::call(self, input2, upper, out); +} +// aten::cholesky_solve.out(Tensor self, Tensor input2, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cholesky_solve_outf(const at::Tensor & self, const at::Tensor & input2, bool upper, at::Tensor & out) { + return at::_ops::cholesky_solve_out::call(self, input2, upper, out); +} + +// aten::cholesky_solve(Tensor self, Tensor input2, bool upper=False) -> Tensor +inline at::Tensor cholesky_solve(const at::Tensor & self, const at::Tensor & input2, bool upper=false) { + return at::_ops::cholesky_solve::call(self, input2, upper); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max.h new file mode 100644 index 0000000000000000000000000000000000000000..5b8d5495ec56423573a11933c725d27536308a6c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max.h @@ -0,0 +1,69 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::clamp_max(Tensor self, Scalar max) -> Tensor +inline at::Tensor clamp_max(const at::Tensor & self, const at::Scalar & max) { + return at::_ops::clamp_max::call(self, max); +} + +// aten::clamp_max.Tensor(Tensor self, Tensor max) -> Tensor +inline at::Tensor clamp_max(const at::Tensor & self, const at::Tensor & max) { + return at::_ops::clamp_max_Tensor::call(self, max); +} + +// aten::clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!) +inline at::Tensor & clamp_max_(at::Tensor & self, const at::Scalar & max) { + return at::_ops::clamp_max_::call(self, max); +} + +// aten::clamp_max_.Tensor(Tensor(a!) self, Tensor max) -> Tensor(a!) +inline at::Tensor & clamp_max_(at::Tensor & self, const at::Tensor & max) { + return at::_ops::clamp_max__Tensor::call(self, max); +} + +// aten::clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clamp_max_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & max) { + return at::_ops::clamp_max_out::call(self, max, out); +} +// aten::clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clamp_max_outf(const at::Tensor & self, const at::Scalar & max, at::Tensor & out) { + return at::_ops::clamp_max_out::call(self, max, out); +} + +// aten::clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clamp_max_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & max) { + return at::_ops::clamp_max_Tensor_out::call(self, max, out); +} +// aten::clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clamp_max_outf(const at::Tensor & self, const at::Tensor & max, at::Tensor & out) { + return at::_ops::clamp_max_Tensor_out::call(self, max, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4aa59d0150053b087283940e9612c80a78b9d4fb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API clamp_max { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_max"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "clamp_max(Tensor self, Scalar max) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & max); +}; + +struct TORCH_API clamp_max_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_max"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "clamp_max.Tensor(Tensor self, Tensor max) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & max); +}; + +struct TORCH_API clamp_max_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_max_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & max); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & max); +}; + +struct TORCH_API clamp_max__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_max_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "clamp_max_.Tensor(Tensor(a!) self, Tensor max) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & max); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & max); +}; + +struct TORCH_API clamp_max_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_max"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & max, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & max, at::Tensor & out); +}; + +struct TORCH_API clamp_max_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_max"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & max, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & max, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..7d1a7ed559b82512161fc06fcfcf343d36279ec6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_meta.h @@ -0,0 +1,37 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_clamp : public TensorIteratorBase { + + + void meta(const at::Tensor & self, at::OptionalScalarRef min, at::OptionalScalarRef max); +}; +struct TORCH_API structured_clamp_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, at::OptionalTensorRef min, at::OptionalTensorRef max); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..222b69f1b236e3cb28301e3fa54b1432f4895629 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_meta_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor clamp(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max=::std::nullopt); +TORCH_API at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max=::std::nullopt); +TORCH_API at::Tensor & clamp_outf(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); +TORCH_API at::Tensor & clamp_(at::Tensor & self, const ::std::optional & min, const ::std::optional & max=::std::nullopt); +TORCH_API at::Tensor clamp(const at::Tensor & self, const ::std::optional & min={}, const ::std::optional & max={}); +TORCH_API at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & min={}, const ::std::optional & max={}); +TORCH_API at::Tensor & clamp_outf(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); +TORCH_API at::Tensor & clamp_(at::Tensor & self, const ::std::optional & min={}, const ::std::optional & max={}); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00c28d1af760303ea2a227b0272c69504bac4096 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Tensor & min); +TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Tensor & min); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..741373242dc24decbe3062b9a9eb943315f48068 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Scalar & min, at::Tensor & out); +TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Tensor & min); +TORCH_API at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & min); +TORCH_API at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Tensor & min, at::Tensor & out); +TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Tensor & min); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clone_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clone_native.h new file mode 100644 index 0000000000000000000000000000000000000000..330342a69c249c6e90980421d189ff46fb169a56 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clone_native.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & clone_out(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor clone_nested(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor clone_sparse(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor clone_sparse_compressed(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor mkldnn_clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor quantized_clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..14a9cc315eafe94fdce1844b93bd82873c13d6f9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor col_indices(const at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..855f3378a99604bb01b75e4f919a9ab77fc030ba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor complex(const at::Tensor & real, const at::Tensor & imag); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..763b2e03227f35da577b177daedcab2a224b1e59 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & complex_out(at::Tensor & out, const at::Tensor & real, const at::Tensor & imag); +TORCH_API at::Tensor & complex_outf(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9625e559333ac1b9cf873061022b34b2e46976d8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & complex_out(at::Tensor & out, const at::Tensor & real, const at::Tensor & imag); +TORCH_API at::Tensor & complex_outf(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ef366ceaaeb9005e63ad90257051683047b2ae07 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API conj { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conj"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conj(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..50469287db15c50bcde8131b562fda76bba765be --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & conj_physical_(at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..811ec843694d98ce032301370755b64878062680 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API conj_physical { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conj_physical"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conj_physical(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API conj_physical_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conj_physical"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API conj_physical_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conj_physical_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conj_physical_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b56599163144d903057c87e3e3f949fdbc6d428f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor contiguous(const at::Tensor & self, at::MemoryFormat memory_format=c10::MemoryFormat::Contiguous); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv1d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv1d.h new file mode 100644 index 0000000000000000000000000000000000000000..561a8bfa21d4d5121ef2a5b0e8c3a218dcdf650d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv1d.h @@ -0,0 +1,75 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::conv1d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, SymInt[1] padding=0, SymInt[1] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv1d::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv1d::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::conv1d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, SymInt[1] padding=0, SymInt[1] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv1d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv1d::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv1d::call(input, weight, bias, stride, padding, dilation, groups); + } +} + +// aten::conv1d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, str padding="valid", SymInt[1] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv1d_padding::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv1d_padding::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::conv1d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, str padding="valid", SymInt[1] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv1d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv1d_padding::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv1d_padding::call(input, weight, bias, stride, padding, dilation, groups); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv2d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..18c6ce2464441f73c7c4206bbdf7ff88b2cb2338 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv2d_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor conv2d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1); +TORCH_API at::Tensor conv2d_padding_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::string_view padding="valid", c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv3d.h new file mode 100644 index 0000000000000000000000000000000000000000..27b250f5ec11fab056b775a99fe4474d12abda9d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv3d.h @@ -0,0 +1,75 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::conv3d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv3d::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv3d::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::conv3d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv3d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv3d::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv3d::call(input, weight, bias, stride, padding, dilation, groups); + } +} + +// aten::conv3d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, str padding="valid", SymInt[3] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv3d_padding::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv3d_padding::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::conv3d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, str padding="valid", SymInt[3] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv3d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv3d_padding::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv3d_padding::call(input, weight, bias, stride, padding, dilation, groups); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..098f63214ca4b5301bf9ccb99924ab823460c50b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API conv_tbc_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv_tbc_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conv_tbc_backward(Tensor self, Tensor input, Tensor weight, Tensor bias, int pad) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & bias, int64_t pad); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & bias, int64_t pad); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1712d0afc87ee062bf3cd4e9dc4d54f42514ab42 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose3d_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API conv_transpose3d_input { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv_transpose3d"; + static constexpr const char* overload_name = "input"; + static constexpr const char* schema_str = "conv_transpose3d.input(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, SymInt groups=1, SymInt[3] dilation=1) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymInt groups, c10::SymIntArrayRef dilation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymInt groups, c10::SymIntArrayRef dilation); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4fbf45bc80d43266dccda6dc279369431083744c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor copy_sparse_to_sparse(const at::Tensor & self, const at::Tensor & src, bool non_blocking=false); +TORCH_API at::Tensor & copy_sparse_to_sparse_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, bool non_blocking=false); +TORCH_API at::Tensor & copy_sparse_to_sparse_outf(const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bc9ce492c781bce2d82d0d5a81f8f99827d7db9a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor copysign(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & copysign_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & copysign_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bef36a4447aece3d9c2ade7021fc0c65bec145a9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor cos(const at::Tensor & self); +TORCH_API at::Tensor & cos_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1ee411bb2e51308ec72cbcd3aa6cecacb31efd35 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor cos(const at::Tensor & self); +TORCH_API at::Tensor & cos_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & cos_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & cos_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosine_similarity_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosine_similarity_native.h new file mode 100644 index 0000000000000000000000000000000000000000..87bc92c466fb251ff76225b3e967bcb44330bacd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosine_similarity_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor cosine_similarity(const at::Tensor & x1, const at::Tensor & x2, int64_t dim=1, double eps=1e-08); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosine_similarity_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosine_similarity_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d696f8fbc57fa3686144e57a77fbe435be087bc8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosine_similarity_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cosine_similarity { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cosine_similarity"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cosine_similarity(Tensor x1, Tensor x2, int dim=1, float eps=1e-08) -> Tensor"; + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2, int64_t dim, double eps); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, int64_t dim, double eps); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cov.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cov.h new file mode 100644 index 0000000000000000000000000000000000000000..bf109864c17de3123a1126a749d918e6c4eb949e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cov.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cov(Tensor self, *, int correction=1, Tensor? fweights=None, Tensor? aweights=None) -> Tensor +inline at::Tensor cov(const at::Tensor & self, int64_t correction=1, const ::std::optional & fweights={}, const ::std::optional & aweights={}) { + return at::_ops::cov::call(self, correction, fweights, aweights); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices.h new file mode 100644 index 0000000000000000000000000000000000000000..807162ef475fe5f91c30c624d51af68fda23dac4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8f672eadac3c2572b68f5592a1f97d1fa1727abc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & crow_indices_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & crow_indices_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ctc_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ctc_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8433685c3feccd243533c8f2dcf467fea799f8a5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ctc_loss_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, int64_t reduction=at::Reduction::Mean, bool zero_infinity=false); +TORCH_API at::Tensor ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, int64_t reduction=at::Reduction::Mean, bool zero_infinity=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..43f630a0c67cede457b803723079b4e7eae71bcf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & cudnn_affine_grid_generator_backward_out(at::Tensor & out, const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W); +TORCH_API at::Tensor & cudnn_affine_grid_generator_backward_outf(const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..e98f8a29eeaf20c6fdaa3b422b301ba6f2757ac8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple cudnn_batch_norm(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double exponential_average_factor, double epsilon) { + return at::_ops::cudnn_batch_norm::call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); +} + +// aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple cudnn_batch_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double exponential_average_factor, double epsilon) { + return at::_ops::cudnn_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2, out3); +} +// aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple cudnn_batch_norm_outf(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::cudnn_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2, out3); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c5b791dc5a60976e22f298632482ab7c08806a0f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cudnn_batch_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cudnn_batch_norm_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace); +}; + +struct TORCH_API cudnn_batch_norm_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cudnn_batch_norm_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cudnn_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_relu_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..db289263d33b8a830a99fa481c5af583fa3db6ef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_relu_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor cudnn_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor cudnn_convolution_relu_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bc3852a06f664f8492060a19c8f4137dc48b213 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); +TORCH_API at::Tensor cudnn_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..c9e623060f7fa8dae84152f9cdb4354e76291521 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cudnn_grid_sampler_backward(Tensor self, Tensor grid, Tensor grad_output) -> (Tensor grad_self, Tensor grad_grid) +inline ::std::tuple cudnn_grid_sampler_backward(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output) { + return at::_ops::cudnn_grid_sampler_backward::call(self, grid, grad_output); +} + +// aten::cudnn_grid_sampler_backward.out(Tensor self, Tensor grid, Tensor grad_output, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple cudnn_grid_sampler_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output) { + return at::_ops::cudnn_grid_sampler_backward_out::call(self, grid, grad_output, out0, out1); +} +// aten::cudnn_grid_sampler_backward.out(Tensor self, Tensor grid, Tensor grad_output, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple cudnn_grid_sampler_backward_outf(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::cudnn_grid_sampler_backward_out::call(self, grid, grad_output, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fa203d51e82b892d22a1f189b747e235ffb21d4c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cudnn_grid_sampler { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cudnn_grid_sampler"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cudnn_grid_sampler(Tensor self, Tensor grid) -> Tensor output"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & grid); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grid); +}; + +struct TORCH_API cudnn_grid_sampler_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cudnn_grid_sampler"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cudnn_grid_sampler.out(Tensor self, Tensor grid, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & grid, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grid, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod.h new file mode 100644 index 0000000000000000000000000000000000000000..099dc79a832efac8d8b695d8bf4773be336c0c72 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cumprod(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor cumprod(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::cumprod::call(self, dim, dtype); +} + +// aten::cumprod.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cumprod_out(at::Tensor & out, const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::cumprod_out::call(self, dim, dtype, out); +} +// aten::cumprod.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cumprod_outf(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::cumprod_out::call(self, dim, dtype, out); +} + +// aten::cumprod.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor cumprod(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::cumprod_dimname::call(self, dim, dtype); +} + +// aten::cumprod.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cumprod_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::cumprod_dimname_out::call(self, dim, dtype, out); +} +// aten::cumprod.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cumprod_outf(const at::Tensor & self, at::Dimname dim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::cumprod_dimname_out::call(self, dim, dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f4f10e14e0bce656f7d0abe236f88f353fced6f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor cumprod_backward(const at::Tensor & grad, const at::Tensor & input, int64_t dim, const at::Tensor & output); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b8edd9fa6500d41801fb8bd5b40b5cc800e926ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor cumprod(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumprod_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumprod_outf(const at::Tensor & self, at::Dimname dim, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor & cumprod_(at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cd6beb7ea5d8fe84164cdc1e73b1105af853895a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_cumprod : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, int64_t dim, ::std::optional dtype); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4b0b32e9b9d57826de70f811f6b16efc50ce7aa0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cumprod { + using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumprod"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cumprod(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional dtype); +}; + +struct TORCH_API cumprod_ { + using schema = at::Tensor & (at::Tensor &, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumprod_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cumprod_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim, ::std::optional dtype); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, ::std::optional dtype); +}; + +struct TORCH_API cumprod_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumprod"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cumprod.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out); +}; + +struct TORCH_API cumprod_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumprod"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "cumprod.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, ::std::optional dtype); +}; + +struct TORCH_API cumprod__dimname { + using schema = at::Tensor & (at::Tensor &, at::Dimname, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumprod_"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "cumprod_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, at::Dimname dim, ::std::optional dtype); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Dimname dim, ::std::optional dtype); +}; + +struct TORCH_API cumprod_dimname_out { + using schema = at::Tensor & (const at::Tensor &, at::Dimname, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumprod"; + static constexpr const char* overload_name = "dimname_out"; + static constexpr const char* schema_str = "cumprod.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Dimname dim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..89c235de2a4911b3bc88b9a4eba08a3b4a78114b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor cumsum(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumsum_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumsum_outf(const at::Tensor & self, at::Dimname dim, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor & cumsum_(at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumulative_trapezoid_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumulative_trapezoid_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bba23bc24c35b201cd5520f73aa709ffc3e4612d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumulative_trapezoid_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cumulative_trapezoid_x { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumulative_trapezoid"; + static constexpr const char* overload_name = "x"; + static constexpr const char* schema_str = "cumulative_trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & y, const at::Tensor & x, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Tensor & x, int64_t dim); +}; + +struct TORCH_API cumulative_trapezoid_dx { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::cumulative_trapezoid"; + static constexpr const char* overload_name = "dx"; + static constexpr const char* schema_str = "cumulative_trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & y, const at::Scalar & dx, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Scalar & dx, int64_t dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/deg2rad.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/deg2rad.h new file mode 100644 index 0000000000000000000000000000000000000000..717b49de62543603a775729fef5bea29cb4230df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/deg2rad.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::deg2rad(Tensor self) -> Tensor +inline at::Tensor deg2rad(const at::Tensor & self) { + return at::_ops::deg2rad::call(self); +} + +// aten::deg2rad_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & deg2rad_(at::Tensor & self) { + return at::_ops::deg2rad_::call(self); +} + +// aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & deg2rad_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::deg2rad_out::call(self, out); +} +// aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & deg2rad_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::deg2rad_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dense_dim_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dense_dim_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e9dead26f0eaa4ca2e2b4c837d4a1ea970cfb927 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dense_dim_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API int64_t dense_dim(const at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagflat.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagflat.h new file mode 100644 index 0000000000000000000000000000000000000000..cc2144ed54647796567398e1773453bcfbff11f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagflat.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::diagflat(Tensor self, int offset=0) -> Tensor +inline at::Tensor diagflat(const at::Tensor & self, int64_t offset=0) { + return at::_ops::diagflat::call(self, offset); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal.h new file mode 100644 index 0000000000000000000000000000000000000000..735807d0e05e68cb2971a618c9284766359320c0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::diagonal(Tensor(a) self, int offset=0, int dim1=0, int dim2=1) -> Tensor(a) +inline at::Tensor diagonal(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1) { + return at::_ops::diagonal::call(self, offset, dim1, dim2); +} + +// aten::diagonal.Dimname(Tensor(a) self, *, Dimname outdim, Dimname dim1, Dimname dim2, int offset=0) -> Tensor(a) +inline at::Tensor diagonal(const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset=0) { + return at::_ops::diagonal_Dimname::call(self, outdim, dim1, dim2, offset); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e9bb15de06442898b86c4bb48efda98bc945ae3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor diagonal_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor diagonal_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +TORCH_API at::Tensor & diagonal_backward_symint_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dbf1d62140fb293a9fd5bdf17d5f732af648a628 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor diagonal(const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset=0); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter.h new file mode 100644 index 0000000000000000000000000000000000000000..620932ce7f34f59155eb346b33cda05c4a0bad9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::diagonal_scatter(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1) -> Tensor +inline at::Tensor diagonal_scatter(const at::Tensor & self, const at::Tensor & src, int64_t offset=0, int64_t dim1=0, int64_t dim2=1) { + return at::_ops::diagonal_scatter::call(self, src, offset, dim1, dim2); +} + +// aten::diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & diagonal_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t offset=0, int64_t dim1=0, int64_t dim2=1) { + return at::_ops::diagonal_scatter_out::call(self, src, offset, dim1, dim2, out); +} +// aten::diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & diagonal_scatter_outf(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { + return at::_ops::diagonal_scatter_out::call(self, src, offset, dim1, dim2, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5392c9721e9270260bad7c9bca9d8d3c8b7a7a69 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & diagonal_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); +TORCH_API at::Tensor & diagonal_scatter_outf(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diff_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diff_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8842ffe3e65094f653f1f38885e119a3c63f73d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diff_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API diff { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::diff"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "diff(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t n, int64_t dim, const ::std::optional & prepend, const ::std::optional & append); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n, int64_t dim, const ::std::optional & prepend, const ::std::optional & append); +}; + +struct TORCH_API diff_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, const ::std::optional &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::diff"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "diff.out(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t n, int64_t dim, const ::std::optional & prepend, const ::std::optional & append, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n, int64_t dim, const ::std::optional & prepend, const ::std::optional & append, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma.h new file mode 100644 index 0000000000000000000000000000000000000000..851e7348d460221c8de848ba6365432de7700cfe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & digamma_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::digamma_out::call(self, out); +} +// aten::digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & digamma_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::digamma_out::call(self, out); +} + +// aten::digamma(Tensor self) -> Tensor +inline at::Tensor digamma(const at::Tensor & self) { + return at::_ops::digamma::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..311eae7eb025bc93af0d07369d17cd8f8210017f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor digamma(const at::Tensor & self); +TORCH_API at::Tensor & digamma_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & digamma_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & digamma_(at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..69a2a0bd0a08e3846ca308ca1ee0dc9f2c06c630 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/digamma_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API digamma_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::digamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "digamma_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API digamma_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::digamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API digamma { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::digamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "digamma(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div.h new file mode 100644 index 0000000000000000000000000000000000000000..1d141b737498ee3d889f18e58c8effe7b93dd574 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div.h @@ -0,0 +1,87 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::div.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor div(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::div_Tensor::call(self, other); +} + +// aten::div.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::div_out::call(self, other, out); +} +// aten::div.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::div_out::call(self, other, out); +} + +// aten::div.Tensor_mode(Tensor self, Tensor other, *, str? rounding_mode) -> Tensor +inline at::Tensor div(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode) { + return at::_ops::div_Tensor_mode::call(self, other, rounding_mode); +} + +// aten::div.out_mode(Tensor self, Tensor other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode) { + return at::_ops::div_out_mode::call(self, other, rounding_mode, out); +} +// aten::div.out_mode(Tensor self, Tensor other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out) { + return at::_ops::div_out_mode::call(self, other, rounding_mode, out); +} + +// aten::div.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor div(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::div_Scalar::call(self, other); +} + +// aten::div.Scalar_mode(Tensor self, Scalar other, *, str? rounding_mode) -> Tensor +inline at::Tensor div(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode) { + return at::_ops::div_Scalar_mode::call(self, other, rounding_mode); +} + +// aten::div.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::div_Scalar_out::call(self, other, out); +} +// aten::div.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::div_Scalar_out::call(self, other, out); +} + +// aten::div.Scalar_mode_out(Tensor self, Scalar other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode) { + return at::_ops::div_Scalar_mode_out::call(self, other, rounding_mode, out); +} +// aten::div.Scalar_mode_out(Tensor self, Scalar other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & div_outf(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode, at::Tensor & out) { + return at::_ops::div_Scalar_mode_out::call(self, other, rounding_mode, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dropout_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dropout_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fbf3f4548e702ccd80aabfb7615300574b45b20d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dropout_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API dropout { + using schema = at::Tensor (const at::Tensor &, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::dropout"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "dropout(Tensor input, float p, bool train) -> Tensor"; + static at::Tensor call(const at::Tensor & input, double p, bool train); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, bool train); +}; + +struct TORCH_API dropout_ { + using schema = at::Tensor & (at::Tensor &, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::dropout_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, double p, bool train); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, bool train); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..60137fd60754a3ba99baf955dd93f91debadacb5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::vector dsplit(const at::Tensor & self, int64_t sections); +TORCH_API ::std::vector dsplit(const at::Tensor & self, at::IntArrayRef indices); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b0d6c3faed375e5b7269278b1bd9e8d9aaaea7f4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector dsplit(const at::Tensor & self, int64_t sections); +TORCH_API ::std::vector dsplit(const at::Tensor & self, at::IntArrayRef indices); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/einsum.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/einsum.h new file mode 100644 index 0000000000000000000000000000000000000000..fd214640488d0ecfef915d1b8a67070ac0fe18f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/einsum.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::einsum(str equation, Tensor[] tensors, *, int[]? path=None) -> Tensor +inline at::Tensor einsum(c10::string_view equation, at::TensorList tensors, at::OptionalIntArrayRef path=::std::nullopt) { + return at::_ops::einsum::call(equation, tensors, path); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2f5fc16279306cac7921d3676d1f94f7aa115c03 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor elu_backward(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..032cd070d4b98e5e546ad0fb61b7ca2358742791 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor elu_backward(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); +TORCH_API at::Tensor & elu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); +TORCH_API at::Tensor & elu_backward_outf(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_dense_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_dense_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..33322bdc99d28ab16d5558fbf010efb598021192 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_dense_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & embedding_dense_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); +TORCH_API at::Tensor & embedding_dense_backward_outf(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq, at::Tensor & out); +TORCH_API at::Tensor & embedding_dense_backward_symint_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq); +TORCH_API at::Tensor & embedding_dense_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm.h new file mode 100644 index 0000000000000000000000000000000000000000..884429fe107b4da3d41b36063ad27a1473d37d20 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::embedding_renorm_(Tensor(a!) self, Tensor indices, float max_norm, float norm_type) -> Tensor(a!) +inline at::Tensor & embedding_renorm_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { + return at::_ops::embedding_renorm_::call(self, indices, max_norm, norm_type); +} + +// aten::embedding_renorm.out(Tensor self, Tensor indices, float max_norm, float norm_type, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & embedding_renorm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { + return at::_ops::embedding_renorm_out::call(self, indices, max_norm, norm_type, out); +} +// aten::embedding_renorm.out(Tensor self, Tensor indices, float max_norm, float norm_type, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & embedding_renorm_outf(const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type, at::Tensor & out) { + return at::_ops::embedding_renorm_out::call(self, indices, max_norm, norm_type, out); +} + +// aten::embedding_renorm(Tensor self, Tensor indices, float max_norm, float norm_type) -> Tensor +inline at::Tensor embedding_renorm(const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { + return at::_ops::embedding_renorm::call(self, indices, max_norm, norm_type); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..783879ecfcd194fa9cf867dddbcbb12c5c90c800 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & embedding_renorm_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_sparse_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_sparse_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..d18179ada8f7d9a60aa78dabffeed18cbe552d53 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_sparse_backward.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::embedding_sparse_backward(Tensor grad, Tensor indices, int num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor +inline at::Tensor embedding_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq) { + return at::_ops::embedding_sparse_backward::call(grad, indices, num_weights, padding_idx, scale_grad_by_freq); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_like_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_like_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d2f57ba846f7617801c8e682e32b6d7f7a6523b7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_like_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API empty_like { + using schema = at::Tensor (const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::empty_like"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "empty_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API empty_like_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::empty_like"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "empty_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ab0f2932d6233a6e98fb9bc799c8ab63e32b42aa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor empty(at::IntArrayRef size, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +TORCH_API at::Tensor empty_symint(c10::SymIntArrayRef size, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_quantized_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_quantized_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..67383f4182e3e68c8a4585a8321ca5d2b60b4d88 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_quantized_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API empty_quantized { + using schema = at::Tensor (at::IntArrayRef, const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::empty_quantized"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "empty_quantized(int[] size, Tensor qtensor, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor"; + static at::Tensor call(at::IntArrayRef size, const at::Tensor & qtensor, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Tensor & qtensor, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API empty_quantized_out { + using schema = at::Tensor & (at::IntArrayRef, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::empty_quantized"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "empty_quantized.out(int[] size, Tensor qtensor, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::IntArrayRef size, const at::Tensor & qtensor, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Tensor & qtensor, ::std::optional memory_format, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_strided_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_strided_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a1c1de4b1aaa29a53eeb472bf56ad20e32393fa1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_strided_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}); +TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={}); +TORCH_API at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..14f64a706644a7057c93effbad2b5dd09585dbc8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor eq(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & eq_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & eq_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor eq(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & eq_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & eq_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0088635bc480a1f36e29a3e68886846fe1e9d48a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API eq__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::eq_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "eq_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API eq__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::eq_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "eq_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API eq_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::eq"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API eq_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::eq"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "eq.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API eq_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::eq"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API eq_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::eq"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "eq.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..80fdd2fda4ae2f7f62fe4cf34bf9394604f4d322 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor erf(const at::Tensor & self); +TORCH_API at::Tensor & erf_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..993cb235c38f021d25ccfed10279fd8cdd602046 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor erf(const at::Tensor & self); +TORCH_API at::Tensor & erf_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erf_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erf_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c09a795c31a54c29aa0ef32b30c1d2fcc2d54fb9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_native.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_erf_out : public at::meta::structured_erf { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor erf_sparse(const at::Tensor & self); +TORCH_API at::Tensor & erf_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erf_sparse_(at::Tensor & self); +TORCH_API at::Tensor erf_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & erf_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erf_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..ea89cb62028bcbfb349e8956a5067702832cabb7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_erfc : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..35df5e28945c864fedbcb9edc179bba4fa3841df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor erfinv(const at::Tensor & self); +TORCH_API at::Tensor & erfinv_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erfinv_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erfinv_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bfef84efa59cd02e3627d1992ce4e4198760198c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API erfinv { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::erfinv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "erfinv(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API erfinv_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::erfinv_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "erfinv_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API erfinv_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::erfinv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..81c20d6e30fe5396ad1e0e38400bd0b84522adf2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor exp2(const at::Tensor & self); +TORCH_API at::Tensor & exp2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & exp2_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & exp2_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a08b231f475957653ae752e0a34c615629b18b6e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_exp2_out : public at::meta::structured_exp2 { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5831379e59b67259c523cbe26108a172920a742b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_exp : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expm1.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expm1.h new file mode 100644 index 0000000000000000000000000000000000000000..02c0f3c8e62b4df6c05c492cef5eb3ecc76a73e7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expm1.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::expm1(Tensor self) -> Tensor +inline at::Tensor expm1(const at::Tensor & self) { + return at::_ops::expm1::call(self); +} + +// aten::expm1_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & expm1_(at::Tensor & self) { + return at::_ops::expm1_::call(self); +} + +// aten::expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & expm1_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::expm1_out::call(self, out); +} +// aten::expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & expm1_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::expm1_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2e15072f33abf77d2ed3ac85a77eabe357a019e5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API exponential_ { + using schema = at::Tensor & (at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::exponential_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "exponential_(Tensor(a!) self, float lambd=1, *, Generator? generator=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, double lambd, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double lambd, ::std::optional generator); +}; + +struct TORCH_API exponential_out { + using schema = at::Tensor & (const at::Tensor &, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::exponential"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double lambd, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double lambd, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API exponential { + using schema = at::Tensor (const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::exponential"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "exponential(Tensor self, float lambd=1, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, double lambd, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double lambd, ::std::optional generator); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eye.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eye.h new file mode 100644 index 0000000000000000000000000000000000000000..5d80186057961eb054cbea4225f6a3ced4af82f0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eye.h @@ -0,0 +1,207 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor eye(int64_t n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor eye(int64_t n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); + } +} + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor eye(c10::SymInt n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor eye(c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, int64_t m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor eye(int64_t n, int64_t m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, int64_t m, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor eye(int64_t n, int64_t m, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, c10::SymInt m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor eye(c10::SymInt n, c10::SymInt m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, c10::SymInt m, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor eye(c10::SymInt n, c10::SymInt m, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_out(at::Tensor & out, int64_t n) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template >> + at::Tensor & eye_out(at::Tensor & out, int64_t n) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_outf(int64_t n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template >> + at::Tensor & eye_outf(int64_t n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template >> + at::Tensor & eye_out(at::Tensor & out, c10::SymInt n) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_outf(c10::SymInt n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template >> + at::Tensor & eye_outf(c10::SymInt n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template >> + at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template >> + at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n, c10::SymInt m) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template >> + at::Tensor & eye_out(at::Tensor & out, c10::SymInt n, c10::SymInt m) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_outf(c10::SymInt n, c10::SymInt m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template >> + at::Tensor & eye_outf(c10::SymInt n, c10::SymInt m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ac5453c6659ea80b09c33512b19e6faa22b2d45 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple fake_quantize_per_channel_affine_cachemask(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..031fe213560ba91a66249d7d21007d21ee9e568d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fake_quantize_per_channel_affine { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fake_quantize_per_channel_affine"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8979505e2c05a6d54f77cb6df814a9f7b3395b29 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max); +TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..dce4d0b15100106306975bd636d3cf1ca13def1c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fbgemm_linear_int8_weight(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor +inline at::Tensor fbgemm_linear_int8_weight(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias) { + return at::_ops::fbgemm_linear_int8_weight::call(input, weight, packed, col_offsets, weight_scale, weight_zero_point, bias); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_native.h new file mode 100644 index 0000000000000000000000000000000000000000..315dee2e213fb35c6b5d858de893f937615d4a09 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fbgemm_linear_int8_weight_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5a7cec4862145d98830fb8ea80ca7fa7377521dd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input); +TORCH_API at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input, int64_t K, int64_t N); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9e1fd21f1e642a23ae8cab4b0258b166b84a5c4e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fbgemm_pack_quantized_matrix { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fbgemm_pack_quantized_matrix"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fbgemm_pack_quantized_matrix(Tensor input) -> Tensor"; + static at::Tensor call(const at::Tensor & input); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input); +}; + +struct TORCH_API fbgemm_pack_quantized_matrix_KN { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fbgemm_pack_quantized_matrix"; + static constexpr const char* overload_name = "KN"; + static constexpr const char* schema_str = "fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor"; + static at::Tensor call(const at::Tensor & input, int64_t K, int64_t N); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, int64_t K, int64_t N); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1504e7e9802af3b71811343ce0e593d0bb049eb9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fft_fft { + using schema = at::Tensor (const at::Tensor &, ::std::optional, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_fft"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_fft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm); +}; + +struct TORCH_API fft_fft_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, int64_t, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_fft"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq.h new file mode 100644 index 0000000000000000000000000000000000000000..59b09eb49806949b30086ef9a3167254d8178324 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq.h @@ -0,0 +1,49 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_fftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor fft_fftfreq(int64_t n, double d=1.0, at::TensorOptions options={}) { + return at::_ops::fft_fftfreq::call(n, d, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::fft_fftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor fft_fftfreq(int64_t n, double d, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::fft_fftfreq::call(n, d, dtype, layout, device, pin_memory); +} + +// aten::fft_fftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fftfreq_out(at::Tensor & out, int64_t n, double d=1.0) { + return at::_ops::fft_fftfreq_out::call(n, d, out); +} +// aten::fft_fftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fftfreq_outf(int64_t n, double d, at::Tensor & out) { + return at::_ops::fft_fftfreq_out::call(n, d, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ae56cd41d37f6517a21bd1ae477af8dd3b92a4d1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_hfft_symint(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_hfft_symint_out(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfftn.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfftn.h new file mode 100644 index 0000000000000000000000000000000000000000..31a91c471950db5a817a9ffcbf7eb108ae53724f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfftn.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_hfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_hfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_hfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s, dim, norm); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_hfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_hfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_hfftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_hfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_hfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfft_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfft_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..816e386779ad08636d2c279eff9606634b4c4329 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfft_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fft_ihfft { + using schema = at::Tensor (const at::Tensor &, ::std::optional, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_ihfft"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_ihfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm); +}; + +struct TORCH_API fft_ihfft_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, int64_t, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_ihfft"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_ihfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6fa523fec4ad653af455e315f4447e04449e320a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn_compositeimplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_ihfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_ihfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_ihfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_ihfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_ihfftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_ihfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft2_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..973228e10f49ee4f467b18b51678653e6743b4b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft2_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fft_irfft2 { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_irfft2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_irfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm); +}; + +struct TORCH_API fft_irfft2_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_irfft2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_irfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3965c9d3b242f01b3235b2356ca366f0ca913e7d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft_compositeimplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_irfft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_irfft_symint(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_irfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_irfft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_irfft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_irfft_symint_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfftn_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfftn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e6d7703a1bdb820f92ba007c139dee86b1e47674 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfftn_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fft_irfftn { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_irfftn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_irfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm); +}; + +struct TORCH_API fft_irfftn_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_irfftn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_irfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft.h new file mode 100644 index 0000000000000000000000000000000000000000..4981643fd116edd8e23cd307fd8033135d1ceccf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_rfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor +inline at::Tensor fft_rfft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_rfft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_rfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor +inline at::Tensor fft_rfft_symint(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft::call(self, n, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_rfft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft::call(self, n, dim, norm); + } +} + +// aten::fft_rfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_rfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_rfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft_out::call(self, n, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft_out::call(self, n, dim, norm, out); + } +} + +// aten::fft_rfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft_symint_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft_out::call(self, n, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft_out::call(self, n, dim, norm, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2.h new file mode 100644 index 0000000000000000000000000000000000000000..82fc7fae536d91f31f9bdf1e9beec49c82d8fedf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_rfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_rfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_rfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_rfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_rfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2::call(self, s, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_rfft2(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2::call(self, s, dim, norm); + } +} + +// aten::fft_rfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_rfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_rfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft2_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfft2_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_rfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfft2_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfft2_out::call(self, s, dim, norm, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d7cdf9f3fe42adc6e91ca4e8bcc2d59af88abc82 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2_compositeimplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_rfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_rfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_rfft2_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cd86c7437540720b9c75be4ffe317023a2ed3026 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft_compositeimplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_rfft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_rfft_symint(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_rfft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft_symint_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..51b84d6988c912bdcd8025b7ac9e1fe2dfd1f3f0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fft_rfftfreq { + using schema = at::Tensor (int64_t, double, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_rfftfreq"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_rfftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(int64_t n, double d, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, double d, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API fft_rfftfreq_out { + using schema = at::Tensor & (int64_t, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_rfftfreq"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_rfftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t n, double d, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, double d, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..05d9533096ad21298a50b0fda9bd9ed95de32955 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_rfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfftn_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fill_diagonal_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fill_diagonal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b184210318ffe612ebdd43bb2b29df603f85d53b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fill_diagonal_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & fill_diagonal_(at::Tensor & self, const at::Scalar & fill_value, bool wrap=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fill_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fill_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a8412b1555d0c4dee5d213f79502e1c59d0e4cc4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fill_native.h @@ -0,0 +1,38 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fill(const at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_Scalar_out(const at::Tensor & self, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_meta_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_nested_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_sparse_csr_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_quantized_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor fill(const at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_Tensor_out(const at::Tensor & self, const at::Tensor & value, at::Tensor & out); +TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_meta_(at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_nested_(at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_quantized_(at::Tensor & self, const at::Tensor & value); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flatten_dense_tensors.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flatten_dense_tensors.h new file mode 100644 index 0000000000000000000000000000000000000000..ed32a029343bb11c746d11121fc5b0500f6827fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flatten_dense_tensors.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::flatten_dense_tensors(Tensor[] tensors) -> Tensor +inline at::Tensor flatten_dense_tensors(at::TensorList tensors) { + return at::_ops::flatten_dense_tensors::call(tensors); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flip_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flip_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c40d481038300d8019090e25e13cb8c89e16e534 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flip_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API flip { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::flip"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "flip(Tensor self, int[] dims) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dims); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims); +}; + +struct TORCH_API flip_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::flip"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "flip.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor.h new file mode 100644 index 0000000000000000000000000000000000000000..9de9dce55fa3715f8c9d977299300ebd59d3d7f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::floor(Tensor self) -> Tensor +inline at::Tensor floor(const at::Tensor & self) { + return at::_ops::floor::call(self); +} + +// aten::floor_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & floor_(at::Tensor & self) { + return at::_ops::floor_::call(self); +} + +// aten::floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::floor_out::call(self, out); +} +// aten::floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::floor_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide.h new file mode 100644 index 0000000000000000000000000000000000000000..f52f737cc4dbb3b86abf58d66742a9bb2cf06912 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::floor_divide(Tensor self, Tensor other) -> Tensor +inline at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::floor_divide::call(self, other); +} + +// aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::floor_divide_out::call(self, other, out); +} +// aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::floor_divide_out::call(self, other, out); +} + +// aten::floor_divide.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor floor_divide(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::floor_divide_Scalar::call(self, other); +} + +// aten::floor_divide.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::floor_divide_Scalar_out::call(self, other, out); +} +// aten::floor_divide.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::floor_divide_Scalar_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fdfade79e613308e978c7a33e9925d16d4be2e66 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e2b21b83d0f7e6ba903dc5ac21a6edb21b264d35 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c50102b506c42957898eef42f05f44944e4c3e49 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_meta_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ef06696f524b34ad5a3ee03fbb53d3d8d01241fb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fmin { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fmin(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API fmin_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fmin.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da810ad201da3dad74eac669532b639a25fd48ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmod_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5bd71436e6e7239412071a7229bdfe55627ce061 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fmod_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmod"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API fmod_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmod"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "fmod.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API fmod__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmod_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "fmod_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API fmod_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmod"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API fmod_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmod"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "fmod.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API fmod__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fmod_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "fmod_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..2ad777ea645f10828c81e9662fc00b05423dcf92 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_frac : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..220b72dede09b2520a3034d1daef2f50bea7437a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fractional_max_pool3d_output { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fractional_max_pool3d"; + static constexpr const char* overload_name = "output"; + static constexpr const char* schema_str = "fractional_max_pool3d.output(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices); +}; + +struct TORCH_API fractional_max_pool3d { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fractional_max_pool3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fractional_max_pool3d(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34499067bd9339dc98c6e337438c4baf4526eeec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & frobenius_norm_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & frobenius_norm_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ad7c646d8468ffc1df89a4de924842463b529025 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API frobenius_norm_dim { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::frobenius_norm"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim); +}; + +struct TORCH_API frobenius_norm_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::frobenius_norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..bc1fb96600c76981b5dcd08e8142263efffa63cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_gcd : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..032e9f5545827d17a86be5f669886b967a95c62d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_gcd_out : public at::meta::structured_gcd { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..15a46c37f21a7ad3b8e7d32a064b59c86ce8b2ca --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cpu_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..99b635c8d225b67d6d5160f333f37b26a0c64f80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu.h new file mode 100644 index 0000000000000000000000000000000000000000..5d856781359fad53703267957320a680647515ea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self, c10::string_view approximate="none") { + return at::_ops::gelu_out::call(self, approximate, out); +} +// aten::gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & gelu_outf(const at::Tensor & self, c10::string_view approximate, at::Tensor & out) { + return at::_ops::gelu_out::call(self, approximate, out); +} + +// aten::gelu_(Tensor(a!) self, *, str approximate='none') -> Tensor(a!) +inline at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none") { + return at::_ops::gelu_::call(self, approximate); +} + +// aten::gelu(Tensor self, *, str approximate='none') -> Tensor +inline at::Tensor gelu(const at::Tensor & self, c10::string_view approximate="none") { + return at::_ops::gelu::call(self, approximate); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44d0e03a88a5a47b0cf8d6e1d4dd0500535b5259 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor geometric(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & geometric_out(at::Tensor & out, const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & geometric_outf(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e485233958bb31c23f29b497c8da20907b2b659d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor geometric(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & geometric_out(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & geometric_(at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger.h new file mode 100644 index 0000000000000000000000000000000000000000..9f031c7c8b84858b071de8b1fb4eea18dc4ab4fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::ger(Tensor self, Tensor vec2) -> Tensor +inline at::Tensor ger(const at::Tensor & self, const at::Tensor & vec2) { + return at::_ops::ger::call(self, vec2); +} + +// aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ger_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2) { + return at::_ops::ger_out::call(self, vec2, out); +} +// aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ger_outf(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) { + return at::_ops::ger_out::call(self, vec2, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger_native.h new file mode 100644 index 0000000000000000000000000000000000000000..652a8f7de5baf0dc027f3e03f97c1598d42e7a82 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor ger(const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & ger_out(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ef97a4d58e1f5f749fed6e54102a19b84b89774e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API glu_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::glu_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input); +}; + +struct TORCH_API glu_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::glu_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp.h new file mode 100644 index 0000000000000000000000000000000000000000..e4066806c5bb0003d2bf01a2271bee0eb4913915 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor +inline at::Tensor glu_jvp(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim) { + return at::_ops::glu_jvp::call(glu, x, dx, dim); +} + +// aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & glu_jvp_out(at::Tensor & out, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim) { + return at::_ops::glu_jvp_out::call(glu, x, dx, dim, out); +} +// aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & glu_jvp_outf(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out) { + return at::_ops::glu_jvp_out::call(glu, x, dx, dim, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..239c737687c5874d41d35f917da85d2cdb0c00e6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor glu(const at::Tensor & self, int64_t dim=-1); +TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1); +TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..470098e321299921b16bac4f6e8beb14f1818c43 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_compositeimplicitautograd_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..527a75afb360ff943f298dd6e5a6811e312f4a2a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor) +inline ::std::tuple grid_sampler_2d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask) { + return at::_ops::grid_sampler_2d_backward::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask); +} + +// aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple grid_sampler_2d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask) { + return at::_ops::grid_sampler_2d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); +} +// aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple grid_sampler_2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::grid_sampler_2d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2e3ba04a6c92de9c9b84de23b137509c27106ddd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor grid_sampler(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b9a6f11b678fe20b7591793524582bdd5e28d909 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API gru_input { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::TensorList, bool, int64_t, double, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gru"; + static constexpr const char* overload_name = "input"; + static constexpr const char* schema_str = "gru.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); +}; + +struct TORCH_API gru_data { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, bool, int64_t, double, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gru"; + static constexpr const char* overload_name = "data"; + static constexpr const char* schema_str = "gru.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c38a6121c6ebb79f14bcd0738d2a7f647fc3956d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..86970d4cf534c4dc43dfa73d7a32541153b8317c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..033b742e351d28e31c53b9b02a86df9437f0d71c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor hamming_window(int64_t window_length, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_periodic_alpha_out(int64_t window_length, bool periodic, double alpha, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_periodic_alpha_beta_out(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44e40efcac00bd3b785f7e1d7e8f61038788c490 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e7b49a3e190fcf4929dde4b1dd3ecdfec803db8d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_hardsigmoid_backward : public TensorIteratorBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..86f43d49eff0d09e23f1234105df3775b475cf4f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API hardsigmoid_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hardsigmoid_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); +}; + +struct TORCH_API hardsigmoid_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hardsigmoid_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..def19e57eb92043fd23fbdaeca73dc4df9365172 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor hardsigmoid(const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..48f27a1f4f46ea1ed96ea6ed37f9f41170898b4b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor hardsigmoid(const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e7fff6efbcb4c84d0c4429621f6c6d47e284e835 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_hardsigmoid : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..c32b4439bbf5fce5c7dd043a3fa1be1e51a511bd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_heaviside : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & values); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb9ad192e412ea454b7c6ba3d0987fd0563d105c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values); +TORCH_API at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values); +TORCH_API at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out); +TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..87cc472b31b8208f5920ffb1fc0e04b176458e01 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API hinge_embedding_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hinge_embedding_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hinge_embedding_loss(Tensor self, Tensor target, float margin=1.0, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, double margin, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, double margin, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogram_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogram_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..050c9c317819903daf716b02ba792c5f9923c58e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogram_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple histogram(const at::Tensor & self, const at::Tensor & bins, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_out(at::Tensor & hist, at::Tensor & bin_edges, const at::Tensor & self, const at::Tensor & bins, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_outf(const at::Tensor & self, const at::Tensor & bins, const ::std::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); +TORCH_API ::std::tuple histogram(const at::Tensor & self, int64_t bins=100, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_out(at::Tensor & hist, at::Tensor & bin_edges, const at::Tensor & self, int64_t bins=100, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_outf(const at::Tensor & self, int64_t bins, ::std::optional> range, const ::std::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e09b5794388b5e92bb9eecb819aae3bd0fae82f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector hsplit(const at::Tensor & self, int64_t sections); +TORCH_API ::std::vector hsplit(const at::Tensor & self, at::IntArrayRef indices); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hspmm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hspmm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cc51ecf489bd19bcd6b58c57feac6a4ece349a04 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hspmm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API hspmm_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hspmm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out); +}; + +struct TORCH_API hspmm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hspmm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hspmm(Tensor mat1, Tensor mat2) -> Tensor"; + static at::Tensor call(const at::Tensor & mat1, const at::Tensor & mat2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hstack.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hstack.h new file mode 100644 index 0000000000000000000000000000000000000000..3afc8b577723d664a639158fa802b006e5c69a8b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hstack.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::hstack(Tensor[] tensors) -> Tensor +inline at::Tensor hstack(at::TensorList tensors) { + return at::_ops::hstack::call(tensors); +} + +// aten::hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hstack_out(at::Tensor & out, at::TensorList tensors) { + return at::_ops::hstack_out::call(tensors, out); +} +// aten::hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hstack_outf(at::TensorList tensors, at::Tensor & out) { + return at::_ops::hstack_out::call(tensors, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..f9afd897f7092f2f66e8052ef7827bec18d6399f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::huber_loss.out(Tensor self, Tensor target, int reduction=Mean, float delta=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & huber_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0) { + return at::_ops::huber_loss_out::call(self, target, reduction, delta, out); +} +// aten::huber_loss.out(Tensor self, Tensor target, int reduction=Mean, float delta=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & huber_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out) { + return at::_ops::huber_loss_out::call(self, target, reduction, delta, out); +} + +// aten::huber_loss(Tensor self, Tensor target, int reduction=Mean, float delta=1.0) -> Tensor +inline at::Tensor huber_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0) { + return at::_ops::huber_loss::call(self, target, reduction, delta); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..7cf993d48ec0492f9705d5411c38c9fbf25a0eab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::huber_loss_backward.out(Tensor grad_output, Tensor self, Tensor target, int reduction, float delta, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & huber_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta) { + return at::_ops::huber_loss_backward_out::call(grad_output, self, target, reduction, delta, grad_input); +} +// aten::huber_loss_backward.out(Tensor grad_output, Tensor self, Tensor target, int reduction, float delta, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & huber_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & grad_input) { + return at::_ops::huber_loss_backward_out::call(grad_output, self, target, reduction, delta, grad_input); +} + +// aten::huber_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, float delta) -> Tensor +inline at::Tensor huber_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta) { + return at::_ops::huber_loss_backward::call(grad_output, self, target, reduction, delta); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..050cfaec848d66207d7c910eb203afda93245675 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor huber_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..17d4f3472f9050511a1c1520ffc533c332c43a3d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & huber_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta); +TORCH_API at::Tensor & huber_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f0099a10de7a084effc00cf629b4ae3391c691f6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API huber_loss_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::huber_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "huber_loss.out(Tensor self, Tensor target, int reduction=Mean, float delta=1.0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out); +}; + +struct TORCH_API huber_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::huber_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "huber_loss(Tensor self, Tensor target, int reduction=Mean, float delta=1.0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0.h new file mode 100644 index 0000000000000000000000000000000000000000..cd8007daeca986ac042d07a20b1cc3c8eaa9cd5c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::i0(Tensor self) -> Tensor +inline at::Tensor i0(const at::Tensor & self) { + return at::_ops::i0::call(self); +} + +// aten::i0_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & i0_(at::Tensor & self) { + return at::_ops::i0_::call(self); +} + +// aten::i0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & i0_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::i0_out::call(self, out); +} +// aten::i0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & i0_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::i0_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index.h new file mode 100644 index 0000000000000000000000000000000000000000..aaa1abc5bc3e1938c061a1d89ad14b6cc85bfa25 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::index.Tensor(Tensor self, Tensor?[] indices) -> Tensor +inline at::Tensor index(const at::Tensor & self, const c10::List<::std::optional> & indices) { + return at::_ops::index_Tensor::call(self, indices); +} + +// aten::index.Tensor_out(Tensor self, Tensor?[] indices, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_out(at::Tensor & out, const at::Tensor & self, const c10::List<::std::optional> & indices) { + return at::_ops::index_Tensor_out::call(self, indices, out); +} +// aten::index.Tensor_out(Tensor self, Tensor?[] indices, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_outf(const at::Tensor & self, const c10::List<::std::optional> & indices, at::Tensor & out) { + return at::_ops::index_Tensor_out::call(self, indices, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_fill_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_fill_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ccc78edbdc4e941f2420cbb849e2006e7c58b63d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_fill_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & index_fill_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & index_fill_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & value); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..ffef895f5f4680d5a7df76e1bfa89175e9875d3a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_meta.h @@ -0,0 +1,44 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_index_reduce : public at::impl::MetaBase { + + template + struct TORCH_API precompute_out { + + precompute_out set_dim(int64_t value) { + static_assert(DIM == false, "dim already set"); + precompute_out ret; +ret.dim = value; +return ret; + } + + int64_t dim; + }; + using meta_return_ty = precompute_out ; + meta_return_ty meta(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6bf02283793f1b07310f1783149f6e1ac846143f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor index_select(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor & index_select_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor & index_select_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3df244a9f544d493da23a90adfb5aeb2f5b30305 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_native.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor index_select_cpu_(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor & index_select_out_cpu_(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out); +TORCH_API at::Tensor index_select_cuda(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor & index_select_out_cuda(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out); +TORCH_API at::Tensor index_select_sparse_cpu(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor index_select_sparse_cuda(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor index_select_quantized_cpu_(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor index_select_quantized_cuda(const at::Tensor & self, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor index_select(const at::Tensor & self, at::Dimname dim, const at::Tensor & index); +TORCH_API at::Tensor & index_select_out(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/indices_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/indices_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..474975c29d59e68dd06dc20ddff7b7bc2d04e323 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/indices_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & indices_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & indices_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/int_repr_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/int_repr_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..188db1c1994b510b88c4381c7dd59243fe19013e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/int_repr_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & int_repr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & int_repr_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced.h new file mode 100644 index 0000000000000000000000000000000000000000..410919f096cab907de6c4a63d97f70642fc65141 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2c18c86f51ac3984014e2261372839bd36039521 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool is_coalesced_default(const at::Tensor & self); +TORCH_API bool is_coalesced_sparse(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c8bc0f23742c265c1a228e896ffeda3da100df7a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool is_floating_point(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..86be94692260aad3b1f81a002f5dffb1c942655b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API is_floating_point { + using schema = bool (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::is_floating_point"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "is_floating_point(Tensor self) -> bool"; + static bool call(const at::Tensor & self); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e024c5d39f0f9686ec781bff3dd0ced0b57f1c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API bool is_pinned(const at::Tensor & self, ::std::optional device=::std::nullopt); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2502390cc93f4635dcf6c0f307cb0a08d3cdfd32 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool is_pinned(const at::Tensor & self, ::std::optional device=::std::nullopt); +TORCH_API bool is_pinned_sparse_coo(const at::Tensor & self, ::std::optional device=::std::nullopt); +TORCH_API bool is_pinned_sparse_compressed(const at::Tensor & self, ::std::optional device=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_signed_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_signed_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cf37068776274f46951fadb83e558b0a4b8dca18 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_signed_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool is_signed(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_native.h new file mode 100644 index 0000000000000000000000000000000000000000..29f56db48e94344501185cee43825347bde69b5c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor isclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isfinite.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isfinite.h new file mode 100644 index 0000000000000000000000000000000000000000..0eb3aee4ec7455cd6619e2db4c8f6c809a08c1dd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isfinite.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::isfinite(Tensor self) -> Tensor +inline at::Tensor isfinite(const at::Tensor & self) { + return at::_ops::isfinite::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isin_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isin_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..62e2e06c05af477df47b1b5b21b6377831f6d1f4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isin_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor isin(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isposinf_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isposinf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a389e107dca6fe2796fb306c8830e96752f55fff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isposinf_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_isposinf_out : public at::meta::structured_isposinf { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_isposinf(const at::Tensor & self); +TORCH_API at::Tensor isposinf_sparse(const at::Tensor & self); +TORCH_API at::Tensor & isposinf_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor isposinf_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & isposinf_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/istft.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/istft.h new file mode 100644 index 0000000000000000000000000000000000000000..f38a73439f8956e092c231f036fc0808214d5003 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/istft.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor +inline at::Tensor istft(const at::Tensor & self, int64_t n_fft, ::std::optional hop_length=::std::nullopt, ::std::optional win_length=::std::nullopt, const ::std::optional & window={}, bool center=true, bool normalized=false, ::std::optional onesided=::std::nullopt, ::std::optional length=::std::nullopt, bool return_complex=false) { + return at::_ops::istft::call(self, n_fft, hop_length, win_length, window, center, normalized, onesided, length, return_complex); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/item_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/item_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d2e9d43d78af0f8b15381d1e9a84f3c7480339eb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/item_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API item { + using schema = at::Scalar (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::item"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "item(Tensor self) -> Scalar"; + static at::Scalar call(const at::Tensor & self); + static at::Scalar redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc5ae023f412996cdcdeacd37204440a353be72d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_compositeexplicitautograd_dispatch.h @@ -0,0 +1,39 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor kaiser_window(int64_t window_length, at::TensorOptions options={}); +TORCH_API at::Tensor kaiser_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length); +TORCH_API at::Tensor & kaiser_window_outf(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, at::TensorOptions options={}); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length, bool periodic); +TORCH_API at::Tensor & kaiser_window_outf(int64_t window_length, bool periodic, at::Tensor & out); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, at::TensorOptions options={}); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length, bool periodic, double beta); +TORCH_API at::Tensor & kaiser_window_outf(int64_t window_length, bool periodic, double beta, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9ef58ce4285385bdb2ac62efdf5b104dde4db891 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API kaiser_window { + using schema = at::Tensor (int64_t, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kaiser_window"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API kaiser_window_periodic { + using schema = at::Tensor (int64_t, bool, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kaiser_window"; + static constexpr const char* overload_name = "periodic"; + static constexpr const char* schema_str = "kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API kaiser_window_beta { + using schema = at::Tensor (int64_t, bool, double, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kaiser_window"; + static constexpr const char* overload_name = "beta"; + static constexpr const char* schema_str = "kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(int64_t window_length, bool periodic, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API kaiser_window_out { + using schema = at::Tensor & (int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kaiser_window"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t window_length, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out); +}; + +struct TORCH_API kaiser_window_periodic_out { + using schema = at::Tensor & (int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kaiser_window"; + static constexpr const char* overload_name = "periodic_out"; + static constexpr const char* schema_str = "kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t window_length, bool periodic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out); +}; + +struct TORCH_API kaiser_window_beta_out { + using schema = at::Tensor & (int64_t, bool, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kaiser_window"; + static constexpr const char* overload_name = "beta_out"; + static constexpr const char* schema_str = "kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t window_length, bool periodic, double beta, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double beta, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e829fbd6f16103e60cb0f7521585ef661d75b30 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor kl_div(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, bool log_target=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf2c4630c0c5b7abe65f12acbd3e41d42991e864 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple kthvalue_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_outf(const at::Tensor & self, int64_t k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple kthvalue_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..636443e29514f0200bc774c3b9a8451d76669f11 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple kthvalue_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_outf(const at::Tensor & self, int64_t k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple kthvalue_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/l1_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/l1_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f15e34730542528e17ed93b6f1c8ab17e86ac8d2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/l1_loss_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor l1_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/le.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/le.h new file mode 100644 index 0000000000000000000000000000000000000000..d8cb95b007c766aa23c3e24135fb2e73d8e407f3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/le.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::le.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & le_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::le_Scalar_out::call(self, other, out); +} +// aten::le.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & le_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::le_Scalar_out::call(self, other, out); +} + +// aten::le.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor le(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::le_Scalar::call(self, other); +} + +// aten::le.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & le_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::le_Tensor_out::call(self, other, out); +} +// aten::le.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & le_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::le_Tensor_out::call(self, other, out); +} + +// aten::le.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor le(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::le_Tensor::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..9a32c6bae8c5020d17b7d0b1d94aec6e890e48fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::leaky_relu.out(Tensor self, Scalar negative_slope=0.01, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & leaky_relu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & negative_slope=0.01) { + return at::_ops::leaky_relu_out::call(self, negative_slope, out); +} +// aten::leaky_relu.out(Tensor self, Scalar negative_slope=0.01, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & leaky_relu_outf(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out) { + return at::_ops::leaky_relu_out::call(self, negative_slope, out); +} + +// aten::leaky_relu(Tensor self, Scalar negative_slope=0.01) -> Tensor +inline at::Tensor leaky_relu(const at::Tensor & self, const at::Scalar & negative_slope=0.01) { + return at::_ops::leaky_relu::call(self, negative_slope); +} + +// aten::leaky_relu_(Tensor(a!) self, Scalar negative_slope=0.01) -> Tensor(a!) +inline at::Tensor & leaky_relu_(at::Tensor & self, const at::Scalar & negative_slope=0.01) { + return at::_ops::leaky_relu_::call(self, negative_slope); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..07ef30f88c8cc904c8799d2690387a1d1e304d77 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor leaky_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); +TORCH_API at::Tensor & leaky_relu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); +TORCH_API at::Tensor & leaky_relu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fd191a208873053d7b4671337f5b4b9882fd47ae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API leaky_relu_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::leaky_relu_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input); +}; + +struct TORCH_API leaky_relu_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::leaky_relu_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0f0d6e14ccc384357cbb078dbcd38f5339179da8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_leaky_relu : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & negative_slope); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..20df4e662214790ea36bb39c9e624a28a98a4a5a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_cpu_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor & lerp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor & lerp_outf(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, at::Tensor & out); +TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +TORCH_API at::Tensor & lerp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +TORCH_API at::Tensor & lerp_outf(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, at::Tensor & out); +TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b24b921743fa3f296cb07d92224fd5a078f51d6e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_lerp_Scalar : public at::meta::structured_lerp_Scalar { +void impl(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, const at::Tensor & out); +}; +struct TORCH_API structured_lerp_Tensor : public at::meta::structured_lerp_Tensor { +void impl(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_equal.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_equal.h new file mode 100644 index 0000000000000000000000000000000000000000..f2f6c6bb1765b4b52d9343c4df2beba0b440ebc7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_equal.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::less_equal_Scalar_out::call(self, other, out); +} +// aten::less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::less_equal_Scalar_out::call(self, other, out); +} + +// aten::less_equal.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor less_equal(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::less_equal_Scalar::call(self, other); +} + +// aten::less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::less_equal_Tensor_out::call(self, other, out); +} +// aten::less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::less_equal_Tensor_out::call(self, other, out); +} + +// aten::less_equal.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor less_equal(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::less_equal_Tensor::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b9860532bbd499f9dd3098a209cff22ab304188a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API less_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::less"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "less.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API less_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::less"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "less.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API less_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::less"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API less_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::less"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "less.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API less__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::less_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "less_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API less__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::less_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "less_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f2322cd288aeb247682d395a19d7f4ab1deba2ef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_lgamma : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b8d31eb7b0b2c90b53fa1577a296277d104087d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_lgamma_out : public at::meta::structured_lgamma { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3dc1dcc476b59cc56a1329dd3a3b5e22019b1b9f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor lift(const at::Tensor & self); +TORCH_API at::Tensor & lift_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & lift_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..29d4d06c5d34cae4f4252600ad39ba827e3015e8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor lift_fresh_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cb91356730cdcea266ecb94950c166818e3da4a2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API lift_fresh_copy { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::lift_fresh_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "lift_fresh_copy(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API lift_fresh_copy_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::lift_fresh_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "lift_fresh_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6da45673e4c03d44d931663bb8515649e6967494 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API lift_fresh { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::lift_fresh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "lift_fresh(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_native.h new file mode 100644 index 0000000000000000000000000000000000000000..10c8845ea70392b8e083a16b6a99e90df88c4824 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor lift(const at::Tensor & self); +TORCH_API at::Tensor & lift_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross.h new file mode 100644 index 0000000000000000000000000000000000000000..cba01261dff2c3063035e1769c54c612a7f041cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_cross(Tensor self, Tensor other, *, int dim=-1) -> Tensor +inline at::Tensor linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1) { + return at::_ops::linalg_cross::call(self, other, dim); +} + +// aten::linalg_cross.out(Tensor self, Tensor other, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, int64_t dim=-1) { + return at::_ops::linalg_cross_out::call(self, other, dim, out); +} +// aten::linalg_cross.out(Tensor self, Tensor other, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cross_outf(const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out) { + return at::_ops::linalg_cross_out::call(self, other, dim, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fe07b2a5eb9fcdec33ce921f20af02cc13fb7e93 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +TORCH_API at::Tensor & linalg_cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +TORCH_API at::Tensor & linalg_cross_outf(const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d9fb7f8a31aea37813bbc12fed016e0d2dfaf3db --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +TORCH_API at::Tensor & linalg_cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +TORCH_API at::Tensor & linalg_cross_outf(const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eig_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eig_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0a0fa5bb6db19163d9625b03015d185144a2c4f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eig_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple linalg_eig(const at::Tensor & self); +TORCH_API ::std::tuple linalg_eig_out(at::Tensor & eigenvalues, at::Tensor & eigenvectors, const at::Tensor & self); +TORCH_API ::std::tuple linalg_eig_outf(const at::Tensor & self, at::Tensor & eigenvalues, at::Tensor & eigenvectors); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f6cd0813e7fb2d59126dd1ede62bc20a0549d0bf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_inv(const at::Tensor & A); +TORCH_API at::Tensor & linalg_inv_out(at::Tensor & out, const at::Tensor & A); +TORCH_API at::Tensor & linalg_inv_outf(const at::Tensor & A, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4a88c0324c4ed89e245a0fdad461b309dd94367 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_inv { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_inv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_inv(Tensor A) -> Tensor"; + static at::Tensor call(const at::Tensor & A); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A); +}; + +struct TORCH_API linalg_inv_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_inv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_inv.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & A, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..828a97829ba9623897d7d8b49e141f211248b718 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple linalg_ldl_factor(const at::Tensor & self, bool hermitian=false); +TORCH_API ::std::tuple linalg_ldl_factor_out(const at::Tensor & self, bool hermitian, at::Tensor & LD, at::Tensor & pivots); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ddc36f9db7f246a83789c741c50ce803316aa14 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor linalg_ldl_solve(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a468b3c4b635698cb062265ce8ba676193a6571f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor linalg_ldl_solve(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); +TORCH_API at::Tensor & linalg_ldl_solve_out(at::Tensor & out, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); +TORCH_API at::Tensor & linalg_ldl_solve_outf(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0362ee6a722e515ee8818052a3b7f92c34e0e7e1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_linalg_ldl_solve : public at::impl::MetaBase { + + + void meta(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex.h new file mode 100644 index 0000000000000000000000000000000000000000..596fb4a281eb626f2c8dac783bc1103e1f920174 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_lu_factor_ex(Tensor A, *, bool pivot=True, bool check_errors=False) -> (Tensor LU, Tensor pivots, Tensor info) +inline ::std::tuple linalg_lu_factor_ex(const at::Tensor & A, bool pivot=true, bool check_errors=false) { + return at::_ops::linalg_lu_factor_ex::call(A, pivot, check_errors); +} + +// aten::linalg_lu_factor_ex.out(Tensor A, *, bool pivot=True, bool check_errors=False, Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) +inline ::std::tuple linalg_lu_factor_ex_out(at::Tensor & LU, at::Tensor & pivots, at::Tensor & info, const at::Tensor & A, bool pivot=true, bool check_errors=false) { + return at::_ops::linalg_lu_factor_ex_out::call(A, pivot, check_errors, LU, pivots, info); +} +// aten::linalg_lu_factor_ex.out(Tensor A, *, bool pivot=True, bool check_errors=False, Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) +inline ::std::tuple linalg_lu_factor_ex_outf(const at::Tensor & A, bool pivot, bool check_errors, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info) { + return at::_ops::linalg_lu_factor_ex_out::call(A, pivot, check_errors, LU, pivots, info); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a2a83fe6dcae903987d01b0c670a67a3b46c49e6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple linalg_lu_factor_ex(const at::Tensor & A, bool pivot=true, bool check_errors=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..47195dca4ac69bf24720dc37a2edf08b3cae6227 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_linalg_lu_factor_ex : public at::impl::MetaBase { + + + void meta(const at::Tensor & A, bool pivot, bool check_errors); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce106be1ce6a5bf7847d4395256e8f8b9f0e70cf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple linalg_lu(const at::Tensor & A, bool pivot=true); +TORCH_API ::std::tuple linalg_lu_out(at::Tensor & P, at::Tensor & L, at::Tensor & U, const at::Tensor & A, bool pivot=true); +TORCH_API ::std::tuple linalg_lu_outf(const at::Tensor & A, bool pivot, at::Tensor & P, at::Tensor & L, at::Tensor & U); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8692663a03fc7241bcce81cc089970be743eb4b1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor linalg_lu_solve(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); +TORCH_API at::Tensor & linalg_lu_solve_out(at::Tensor & out, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); +TORCH_API at::Tensor & linalg_lu_solve_outf(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7b454aa0a5aeba4cc8f16fb0d8d0aea13730f72f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_linalg_lu_solve_out : public at::meta::structured_linalg_lu_solve { +void impl(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8dc3539fb64a1ab8f44230dc9ad58b78efdee6bc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor linalg_matrix_exp(const at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_multi_dot_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_multi_dot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ab6e912a37a33067f0d8ddebce5c55957e5bb020 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_multi_dot_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_multi_dot(at::TensorList tensors); +TORCH_API at::Tensor & linalg_multi_dot_out(at::TensorList tensors, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_norm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..b3f7e96c67711b4631c42edf1b82b8c130ff57f5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_norm.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_norm(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor linalg_norm(const at::Tensor & self, const ::std::optional & ord=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm::call(self, ord, dim, keepdim, dtype); +} + +// aten::linalg_norm.ord_str(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor linalg_norm(const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm_ord_str::call(self, ord, dim, keepdim, dtype); +} + +// aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & ord=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm_out::call(self, ord, dim, keepdim, dtype, out); +} +// aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_outf(const at::Tensor & self, const ::std::optional & ord, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::linalg_norm_out::call(self, ord, dim, keepdim, dtype, out); +} + +// aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_out(at::Tensor & out, const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm_ord_str_out::call(self, ord, dim, keepdim, dtype, out); +} +// aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_outf(const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::linalg_norm_ord_str_out::call(self, ord, dim, keepdim, dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_qr_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_qr_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0102f1063d0efa4a9475defa29dfef9c525b84c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_qr_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_linalg_qr : public at::impl::MetaBase { + + + void meta(const at::Tensor & A, c10::string_view mode); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_slogdet_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_slogdet_native.h new file mode 100644 index 0000000000000000000000000000000000000000..295f38fcd3e70fe992ea43595bf9082285b88149 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_slogdet_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple linalg_slogdet(const at::Tensor & A); +TORCH_API ::std::tuple linalg_slogdet_out(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..55c6a75315bbaa1a5f311bc5ebca127a6463153b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_solve(const at::Tensor & A, const at::Tensor & B, bool left=true); +TORCH_API at::Tensor & linalg_solve_out(at::Tensor & out, const at::Tensor & A, const at::Tensor & B, bool left=true); +TORCH_API at::Tensor & linalg_solve_outf(const at::Tensor & A, const at::Tensor & B, bool left, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_ex_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_ex_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..989ae736b8212764fc1c9b5a9a4bf8a1512e00e4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_ex_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_solve_ex { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_solve_ex"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor info)"; + static ::std::tuple call(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors); +}; + +struct TORCH_API linalg_solve_ex_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_solve_ex"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_solve_ex.out(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) info) -> (Tensor(a!) result, Tensor(b!) info)"; + static ::std::tuple call(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & info); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & info); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_native.h new file mode 100644 index 0000000000000000000000000000000000000000..05bcb16c10eef0954da53076d7fc610e353442d8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_svdvals(const at::Tensor & A, ::std::optional driver=::std::nullopt); +TORCH_API at::Tensor & linalg_svdvals_out(const at::Tensor & A, ::std::optional driver, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..16a17009813ef2a6ab3c46b3ad6430c43207a0c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_svdvals { + using schema = at::Tensor (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_svdvals"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_svdvals(Tensor A, *, str? driver=None) -> Tensor"; + static at::Tensor call(const at::Tensor & A, ::std::optional driver); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, ::std::optional driver); +}; + +struct TORCH_API linalg_svdvals_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_svdvals"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_svdvals.out(Tensor A, *, str? driver=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & A, ::std::optional driver, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, ::std::optional driver, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander.h new file mode 100644 index 0000000000000000000000000000000000000000..67f14b53f20dcf0f0fd2741268ecd1acfe73f02d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_vander(Tensor x, *, SymInt? N=None) -> Tensor +inline at::Tensor linalg_vander(const at::Tensor & x, ::std::optional N=::std::nullopt) { + return at::_ops::linalg_vander::call(x, N.has_value() ? ::std::make_optional(c10::SymInt(*N)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor linalg_vander(const at::Tensor & x, ::std::optional N=::std::nullopt) { + return at::_ops::linalg_vander::call(x, N.has_value() ? ::std::make_optional(c10::SymInt(*N)) : ::std::nullopt); + } +} + +// aten::linalg_vander(Tensor x, *, SymInt? N=None) -> Tensor +inline at::Tensor linalg_vander_symint(const at::Tensor & x, ::std::optional N=::std::nullopt) { + return at::_ops::linalg_vander::call(x, N); +} +namespace symint { + template >> + at::Tensor linalg_vander(const at::Tensor & x, ::std::optional N=::std::nullopt) { + return at::_ops::linalg_vander::call(x, N); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c44fddb60852d70ef049e91f8ec41be9052c759 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_vander(const at::Tensor & x, ::std::optional N=::std::nullopt); +TORCH_API at::Tensor linalg_vander_symint(const at::Tensor & x, ::std::optional N=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7ae72925cf9c102982e696a20f829173bf2d9790 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vander_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_vander_symint(const at::Tensor & x, ::std::optional N=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..03d5ada076e3442b73c6959a0eee7678b5838ac8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_vecdot(const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_outf(const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..83da3e68d89ebf49b50542eca0a6b27ff7bcebb3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_vecdot { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_vecdot"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_vecdot(Tensor x, Tensor y, *, int dim=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Tensor & y, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & y, int64_t dim); +}; + +struct TORCH_API linalg_vecdot_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_vecdot"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_vecdot.out(Tensor x, Tensor y, *, int dim=-1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log1p_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log1p_native.h new file mode 100644 index 0000000000000000000000000000000000000000..025c9092510e2b6d4b4d94e8190b29935ab61de0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log1p_native.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_log1p_out : public at::meta::structured_log1p { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor log1p_sparse(const at::Tensor & self); +TORCH_API at::Tensor & log1p_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log1p_sparse_(at::Tensor & self); +TORCH_API at::Tensor log1p_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & log1p_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log1p_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log1p_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log1p_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c2de140aebcd4d4e4af4eba82a519d792a7f1b90 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log1p_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API log1p { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::log1p"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "log1p(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API log1p_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::log1p_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "log1p_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API log1p_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::log1p"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2dc0057830fc9a8092e45ef433bf8cefbfde1bc9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor log2(const at::Tensor & self); +TORCH_API at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log2_(at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c3413eb82f38fa4ae414a8c69c5ea3e8d27324d0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_log_out : public at::meta::structured_log { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fe3ccb46eb4082be9da8936764e63812541fd2de --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor log_sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & buffer); +TORCH_API at::Tensor & log_sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & buffer); +TORCH_API at::Tensor & log_sigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & buffer, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_softmax_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..38a619cca10f64fee587ee08c4ed65c3147a74c3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_softmax_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor log_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor log_softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp.h new file mode 100644 index 0000000000000000000000000000000000000000..ad684b102165abafca3994e217e29d030ba83e35 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::logaddexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logaddexp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logaddexp_out::call(self, other, out); +} +// aten::logaddexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logaddexp_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::logaddexp_out::call(self, other, out); +} + +// aten::logaddexp(Tensor self, Tensor other) -> Tensor +inline at::Tensor logaddexp(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logaddexp::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2.h new file mode 100644 index 0000000000000000000000000000000000000000..34b6706df7fc2f21b0e063143a195248d9b7f43f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logaddexp2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logaddexp2_out::call(self, other, out); +} +// aten::logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logaddexp2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::logaddexp2_out::call(self, other, out); +} + +// aten::logaddexp2(Tensor self, Tensor other) -> Tensor +inline at::Tensor logaddexp2(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logaddexp2::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b12c09dd34eca0e5badcd52e906a82b01b45a9f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor logaddexp2(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a0502d79031fd0cdeb6cf72e2700f8cef890115 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor logaddexp2(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logcumsumexp_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logcumsumexp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..34fc2a808efa0afdaf1571f6c09b775d1715c623 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logcumsumexp_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor logcumsumexp(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & logcumsumexp_out(const at::Tensor & self, int64_t dim, at::Tensor & out); +TORCH_API at::Tensor logcumsumexp(const at::Tensor & self, at::Dimname dim); +TORCH_API at::Tensor & logcumsumexp_out(const at::Tensor & self, at::Dimname dim, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logdet.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logdet.h new file mode 100644 index 0000000000000000000000000000000000000000..d6c53f4ae8273f995c374a76c7f49ac668d3fe0b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logdet.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::logdet(Tensor self) -> Tensor +inline at::Tensor logdet(const at::Tensor & self) { + return at::_ops::logdet::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logdet_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logdet_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1414f715d794b7156391c71f855367945dc64bb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logdet_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API logdet { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::logdet"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "logdet(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa9cd5574ef325be7171c5e9f7eeb8133f8669ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e35cbb8237a17f67e44f474383e6b4a5e8375a12 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1e089bc4e7884d15883cddd47f320577c00fbf5c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor logical_not(const at::Tensor & self); +TORCH_API at::Tensor & logical_not_(at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not_native.h new file mode 100644 index 0000000000000000000000000000000000000000..49047e250b35218bd0141db92ddb52b58c5aa5fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor logical_not(const at::Tensor & self); +TORCH_API at::Tensor & logical_not_(at::Tensor & self); +TORCH_API at::Tensor & logical_not_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor NestedTensor_logical_not(const at::Tensor & self); +TORCH_API at::Tensor & NestedTensor_logical_not_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..45fd1679f41f4fedc9a5a9a5a3ceb433b9a4efaf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & logical_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63e658d6387e8faf6e931420140a2767d2c7d606 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API logical_or { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::logical_or"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "logical_or(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API logical_or_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::logical_or_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "logical_or_(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API logical_or_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::logical_or"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_xor_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_xor_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9cea312ae4ba6b55d3a33bd4225e306f1a75d8b1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_xor_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & logical_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..76fb48a308e7d467bd2ffa7ba83cf26cb9a730ef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor logit(const at::Tensor & self, ::std::optional eps=::std::nullopt); +TORCH_API at::Tensor & logit_out(const at::Tensor & self, ::std::optional eps, at::Tensor & out); +TORCH_API at::Tensor & logit_(at::Tensor & self, ::std::optional eps=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lstm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lstm.h new file mode 100644 index 0000000000000000000000000000000000000000..454c7e9684b57b8a74ee4de1b097c9abc4b71638 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lstm.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::lstm.input(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor) +inline ::std::tuple lstm(const at::Tensor & input, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) { + return at::_ops::lstm_input::call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); +} + +// aten::lstm.data(Tensor data, Tensor batch_sizes, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor, Tensor) +inline ::std::tuple lstm(const at::Tensor & data, const at::Tensor & batch_sizes, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) { + return at::_ops::lstm_data::call(data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve.h new file mode 100644 index 0000000000000000000000000000000000000000..48ec807f26fc79ae195430d7a206a4a7ce16e32e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lu_solve_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots) { + return at::_ops::lu_solve_out::call(self, LU_data, LU_pivots, out); +} +// aten::lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lu_solve_outf(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out) { + return at::_ops::lu_solve_out::call(self, LU_data, LU_pivots, out); +} + +// aten::lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor +inline at::Tensor lu_solve(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots) { + return at::_ops::lu_solve::call(self, LU_data, LU_pivots); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e15a25c12e713c201608e6f308eeea5644863a95 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor lu_solve(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots); +TORCH_API at::Tensor & lu_solve_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots); +TORCH_API at::Tensor & lu_solve_outf(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e9ece371a9c7eefe9f2b80efda795d3248d024e5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple lu_unpack(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7291e738323b5048a5e42bce076e59af78e141f3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple lu_unpack(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true); +TORCH_API ::std::tuple lu_unpack_out(at::Tensor & P, at::Tensor & L, at::Tensor & U, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true); +TORCH_API ::std::tuple lu_unpack_outf(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7c7692dccbae8cf430deee077aa77993c4a0b9cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor masked_scatter_backward(const at::Tensor & grad_output, const at::Tensor & mask, at::IntArrayRef sizes); +TORCH_API at::Tensor masked_scatter_backward_symint(const at::Tensor & grad_output, const at::Tensor & mask, c10::SymIntArrayRef sizes); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa3d9cd656c690ee8ba1ed3b40a60030b5a691a3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor masked_scatter(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); +TORCH_API at::Tensor & masked_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); +TORCH_API at::Tensor & masked_scatter_outf(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ffcc5a3501559667389b789183a7e38319000c1b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor masked_scatter(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); +TORCH_API at::Tensor & masked_scatter_out(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source, at::Tensor & out); +TORCH_API at::Tensor & masked_scatter__cpu(at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); +TORCH_API at::Tensor & masked_scatter__cuda(at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..66a1b11e3eab98e0adc378a55833060f1180dc22 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::matmul_backward(Tensor grad, Tensor self, Tensor other, bool[2] mask) -> (Tensor, Tensor) +inline ::std::tuple matmul_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array mask) { + return at::_ops::matmul_backward::call(grad, self, other, mask); +} + +// aten::matmul_backward.out(Tensor grad, Tensor self, Tensor other, bool[2] mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple matmul_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array mask) { + return at::_ops::matmul_backward_out::call(grad, self, other, mask, out0, out1); +} +// aten::matmul_backward.out(Tensor grad, Tensor self, Tensor other, bool[2] mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple matmul_backward_outf(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::matmul_backward_out::call(grad, self, other, mask, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5703aed0a370c3e3ff8e460e40dacb2cdcd9552b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor matmul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & matmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & matmul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7c350897170b58f9cbcf9b33af34b9ff1abc02cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API matmul { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::matmul"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "matmul(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API matmul_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::matmul"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..170a276e52e62ba2f0a93749426525812e01bb5d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & max_pool2d_with_indices_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices) { + return at::_ops::max_pool2d_with_indices_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices, grad_input); +} +// aten::max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & max_pool2d_with_indices_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input) { + return at::_ops::max_pool2d_with_indices_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices, grad_input); +} + +// aten::max_pool2d_with_indices_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices) -> Tensor +inline at::Tensor max_pool2d_with_indices_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices) { + return at::_ops::max_pool2d_with_indices_backward::call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9d98a876bdc1a95b02d86c3b6336109ffd7adfd7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_max_pool2d_with_indices_backward_out_cpu : public at::meta::structured_max_pool2d_with_indices_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, const at::Tensor & grad_input); +}; +struct TORCH_API structured_max_pool2d_with_indices_backward_out_cuda : public at::meta::structured_max_pool2d_with_indices_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5a1b521df218186e05aac90ad748f3a676ee6c3f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API max_pool2d_with_indices_out { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::max_pool2d_with_indices"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); +}; + +struct TORCH_API max_pool2d_with_indices { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::max_pool2d_with_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1fad83236c8e920097331bc3dfde54cbfc509911 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple max_pool3d_with_indices(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API ::std::tuple max_pool3d_with_indices_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API ::std::tuple max_pool3d_with_indices_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool2d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..38ba63aad9af744f33ec90dabf11ac48063899dc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool2d.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template >> + at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template >> + at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); +} +namespace symint { + template >> + at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); + } +} + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_symint_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); +} +namespace symint { + template >> + at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); + } +} + +// aten::max_unpool2d(Tensor self, Tensor indices, SymInt[2] output_size) -> Tensor +inline at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, c10::fromIntArrayRefSlow(output_size)); +} +namespace symint { + template >> + at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, c10::fromIntArrayRefSlow(output_size)); + } +} + +// aten::max_unpool2d(Tensor self, Tensor indices, SymInt[2] output_size) -> Tensor +inline at::Tensor max_unpool2d_symint(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, output_size); +} +namespace symint { + template >> + at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, output_size); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool2d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8f1a36664e703f8026b76afc05b08a67a7dd6bff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool2d_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size); +TORCH_API at::Tensor max_unpool2d_symint(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size); +TORCH_API at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size); +TORCH_API at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor & max_unpool2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size); +TORCH_API at::Tensor & max_unpool2d_symint_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..d3801bbd538eed9de7b85f4f7c9704fcf81e343e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::max_unpool3d.out(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), stride, padding, out); +} +namespace symint { + template >> + at::Tensor & max_unpool3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), stride, padding, out); + } +} + +// aten::max_unpool3d.out(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool3d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::max_unpool3d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), stride, padding, out); +} +namespace symint { + template >> + at::Tensor & max_unpool3d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::max_unpool3d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), stride, padding, out); + } +} + +// aten::max_unpool3d.out(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d_out::call(self, indices, output_size, stride, padding, out); +} +namespace symint { + template >> + at::Tensor & max_unpool3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d_out::call(self, indices, output_size, stride, padding, out); + } +} + +// aten::max_unpool3d.out(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool3d_symint_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::max_unpool3d_out::call(self, indices, output_size, stride, padding, out); +} +namespace symint { + template >> + at::Tensor & max_unpool3d_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::max_unpool3d_out::call(self, indices, output_size, stride, padding, out); + } +} + +// aten::max_unpool3d(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding) -> Tensor +inline at::Tensor max_unpool3d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d::call(self, indices, c10::fromIntArrayRefSlow(output_size), stride, padding); +} +namespace symint { + template >> + at::Tensor max_unpool3d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d::call(self, indices, c10::fromIntArrayRefSlow(output_size), stride, padding); + } +} + +// aten::max_unpool3d(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding) -> Tensor +inline at::Tensor max_unpool3d_symint(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d::call(self, indices, output_size, stride, padding); +} +namespace symint { + template >> + at::Tensor max_unpool3d(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::max_unpool3d::call(self, indices, output_size, stride, padding); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum.h new file mode 100644 index 0000000000000000000000000000000000000000..d650e970b0267dfb4ba069e5bf2b31110a73f3d2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::maximum(Tensor self, Tensor other) -> Tensor +inline at::Tensor maximum(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::maximum::call(self, other); +} + +// aten::maximum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & maximum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::maximum_out::call(self, other, out); +} +// aten::maximum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & maximum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::maximum_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..240825ac4ed896f6f6e63dc7f33e9f8811aeb5c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor maximum(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & maximum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & maximum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean.h new file mode 100644 index 0000000000000000000000000000000000000000..79b3eb18b1cfbd5091f526173ba00cb4d09c2946 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mean(Tensor self, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor mean(const at::Tensor & self, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean::call(self, dtype); +} + +// aten::mean.dtype_out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_dtype_out::call(self, dtype, out); +} +// aten::mean.dtype_out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_outf(const at::Tensor & self, ::std::optional dtype, at::Tensor & out) { + return at::_ops::mean_dtype_out::call(self, dtype, out); +} + +// aten::mean.dim(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_dim::call(self, dim, keepdim, dtype); +} + +// aten::mean.out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_out::call(self, dim, keepdim, dtype, out); +} +// aten::mean.out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::mean_out::call(self, dim, keepdim, dtype, out); +} + +// aten::mean.names_dim(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor mean(const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_names_dim::call(self, dim, keepdim, dtype); +} + +// aten::mean.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_names_out::call(self, dim, keepdim, dtype, out); +} +// aten::mean.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_outf(const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::mean_names_out::call(self, dim, keepdim, dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fd8b1963efe6396bde2217caa8200a53d1a6473e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & mean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ce974cc26b444d9c9531e8582864e304ab6cf44a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mean { + using schema = at::Tensor (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mean"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mean(Tensor self, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype); +}; + +struct TORCH_API mean_dtype_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mean"; + static constexpr const char* overload_name = "dtype_out"; + static constexpr const char* schema_str = "mean.dtype_out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, at::Tensor & out); +}; + +struct TORCH_API mean_dim { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mean"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "mean.dim(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API mean_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mean"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mean.out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +}; + +struct TORCH_API mean_names_dim { + using schema = at::Tensor (const at::Tensor &, at::DimnameList, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mean"; + static constexpr const char* overload_name = "names_dim"; + static constexpr const char* schema_str = "mean.names_dim(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API mean_names_out { + using schema = at::Tensor & (const at::Tensor &, at::DimnameList, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mean"; + static constexpr const char* overload_name = "names_out"; + static constexpr const char* schema_str = "mean.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/median.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/median.h new file mode 100644 index 0000000000000000000000000000000000000000..d223addd2b27bda52d4b3ac16b5cb80b9d7834b9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/median.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::median(Tensor self) -> Tensor +inline at::Tensor median(const at::Tensor & self) { + return at::_ops::median::call(self); +} + +// aten::median.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple median(const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::median_dim::call(self, dim, keepdim); +} + +// aten::median.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple median_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::median_dim_values::call(self, dim, keepdim, values, indices); +} +// aten::median.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple median_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::median_dim_values::call(self, dim, keepdim, values, indices); +} + +// aten::median.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple median(const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::median_names_dim::call(self, dim, keepdim); +} + +// aten::median.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple median_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::median_names_dim_values::call(self, dim, keepdim, values, indices); +} +// aten::median.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple median_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::median_names_dim_values::call(self, dim, keepdim, values, indices); +} + +// aten::median.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & median_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::median_out::call(self, out); +} +// aten::median.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & median_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::median_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..911323fa906851cac551c217b53fc5ae636760e1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple min(const at::Tensor & self, int64_t dim, bool keepdim=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a69824da016224e56214b693603bbfec224a4aa8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_native.h @@ -0,0 +1,37 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_min_out : public at::meta::structured_min_dim { +void impl(const at::Tensor & self, int64_t dim, bool keepdim, const at::Tensor & min, const at::Tensor & min_indices); +}; +TORCH_API ::std::tuple qmin(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple min(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple min_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); +TORCH_API at::Tensor min(const at::Tensor & self); +TORCH_API at::Tensor & min_unary_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor min_quantized_cpu(const at::Tensor & self); +TORCH_API at::Tensor & min_quantized_unary_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor min(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & min_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2ef6621381e6624e6bf2ff465dc95fb24c7d1aa6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_ops.h @@ -0,0 +1,111 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API min_dim { + using schema = ::std::tuple (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "min.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim); +}; + +struct TORCH_API min_dim_min { + using schema = ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "dim_min"; + static constexpr const char* schema_str = "min.dim_min(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) min, Tensor(b!) min_indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); +}; + +struct TORCH_API min_names_dim { + using schema = ::std::tuple (const at::Tensor &, at::Dimname, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "names_dim"; + static constexpr const char* schema_str = "min.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim); +}; + +struct TORCH_API min_names_dim_min { + using schema = ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "names_dim_min"; + static constexpr const char* schema_str = "min.names_dim_min(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) min, Tensor(b!) min_indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); +}; + +struct TORCH_API min { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "min(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API min_unary_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "unary_out"; + static constexpr const char* schema_str = "min.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API min_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API min_other { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::min"; + static constexpr const char* overload_name = "other"; + static constexpr const char* schema_str = "min.other(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/minimum_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/minimum_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..916b37aa9b9f9fc9c97b84f9591379103bfcbfc6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/minimum_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor minimum(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & minimum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & minimum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_batch_norm_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_batch_norm_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..58731f253aed5227c2fe709271cf8e9929580638 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_batch_norm_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple miopen_batch_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon); +TORCH_API ::std::tuple miopen_batch_norm_backward_outf(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c23a22e039712ca29fc5167bfc8ad56f87cef493 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor miopen_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..85f0e0f71c0eabf5c60e970ed075cfa158c550e9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor miopen_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e5fec9e701c09c7d3f97b092081146c5798c6f46 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_depthwise_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3938591bfc106f4468e619e71b74de522f50d652 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & miopen_depthwise_convolution_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..de51fd2e93a5c688ea8610947af1db66f1360596 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API miopen_rnn_backward { + using schema = ::std::tuple> (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &, const at::Tensor &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[])"; + static ::std::tuple> call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); + static ::std::tuple> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +}; + +struct TORCH_API miopen_rnn_backward_out { + using schema = void (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &, const at::Tensor &, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> ()"; + static void call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5714fd52fcde4ba1cacd28dd4eae662fe5d43a66 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API miopen_rnn { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +}; + +struct TORCH_API miopen_rnn_out { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))"; + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1fd884449af949c055df01bdb4e458cd34216b14 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor mish(const at::Tensor & self); +TORCH_API at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & mish_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..02a8df770629398239a3b0d0b82f9b31aa981e11 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor +inline at::Tensor mkldnn_adaptive_avg_pool2d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::mkldnn_adaptive_avg_pool2d::call(self, output_size); +} + +// aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_adaptive_avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::mkldnn_adaptive_avg_pool2d_out::call(self, output_size, out); +} +// aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_adaptive_avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::mkldnn_adaptive_avg_pool2d_out::call(self, output_size, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_convolution_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d53a2f0c2740b2fbd08fe31e9b5d10583b0082f1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_convolution_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor & mkldnn_convolution_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input.h new file mode 100644 index 0000000000000000000000000000000000000000..1615eec302a1754d94da02d1925b6933070a0bcf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_linear_backward_input(int[] input_size, Tensor grad_output, Tensor weight) -> Tensor +inline at::Tensor mkldnn_linear_backward_input(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight) { + return at::_ops::mkldnn_linear_backward_input::call(input_size, grad_output, weight); +} + +// aten::mkldnn_linear_backward_input.out(int[] input_size, Tensor grad_output, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_linear_backward_input_out(at::Tensor & out, at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight) { + return at::_ops::mkldnn_linear_backward_input_out::call(input_size, grad_output, weight, out); +} +// aten::mkldnn_linear_backward_input.out(int[] input_size, Tensor grad_output, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_linear_backward_input_outf(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out) { + return at::_ops::mkldnn_linear_backward_input_out::call(input_size, grad_output, weight, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_native.h new file mode 100644 index 0000000000000000000000000000000000000000..15c32557261103be1fbaf1264f6e496671486fc9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & mkldnn_linear_backward_input_out(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out); +TORCH_API at::Tensor mkldnn_linear_backward_input(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..18ac262369ad4ed789641b1662f12efa8e699c14 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor mkldnn_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::mkldnn_max_pool3d_backward::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool3d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::mkldnn_max_pool3d_backward_out::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { + return at::_ops::mkldnn_max_pool3d_backward_out::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..20f223a3dfeb8b3bb1b7565191176ee8b2bd2798 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mkldnn_max_pool3d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool3d_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm.h new file mode 100644 index 0000000000000000000000000000000000000000..7454f0d6d04e1da322db8368ee58d3062291d1c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mm(Tensor self, Tensor mat2) -> Tensor +inline at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::mm::call(self, mat2); +} + +// aten::mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::mm_out::call(self, mat2, out); +} +// aten::mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::mm_out::call(self, mat2, out); +} + +// aten::mm.dtype(Tensor self, Tensor mat2, ScalarType out_dtype) -> Tensor +inline at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype) { + return at::_ops::mm_dtype::call(self, mat2, out_dtype); +} + +// aten::mm.dtype_out(Tensor self, Tensor mat2, ScalarType out_dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype) { + return at::_ops::mm_dtype_out::call(self, mat2, out_dtype, out); +} +// aten::mm.dtype_out(Tensor self, Tensor mat2, ScalarType out_dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out) { + return at::_ops::mm_dtype_out::call(self, mat2, out_dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aa484a8c2807542af1d168ed3b129440cfb9f722 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1f864d3baea0792ac7a2b636b1a2f8c80835424a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_native.h @@ -0,0 +1,37 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_mm_out_cpu : public at::meta::structured_mm { +void impl(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & out); +}; +struct TORCH_API structured_mm_out_cuda : public at::meta::structured_mm { +void impl(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & out); +}; +TORCH_API at::Tensor _sparse_mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _sparse_mm_out(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _sparse_csr_mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _sparse_csr_mm_out(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _mm_dtype_cuda(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & _mm_dtype_out_cuda(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode.h new file mode 100644 index 0000000000000000000000000000000000000000..6e647a4c64a302d13358eca7bc7fc80e4e3abbb3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false) { + return at::_ops::mode::call(self, dim, keepdim); +} + +// aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim=-1, bool keepdim=false) { + return at::_ops::mode_values::call(self, dim, keepdim, values, indices); +} +// aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::mode_values::call(self, dim, keepdim, values, indices); +} + +// aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::mode_dimname::call(self, dim, keepdim); +} + +// aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::mode_dimname_out::call(self, dim, keepdim, values, indices); +} +// aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::mode_dimname_out::call(self, dim, keepdim, values, indices); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7747614a9331d7ae96eff54f71406f561e3ec752 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple mode_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_native.h new file mode 100644 index 0000000000000000000000000000000000000000..74169f11d519a492c2479553524d6f021415a3df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple mode_out(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple mode_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/moveaxis_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/moveaxis_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0d620442ca9e6797f63a0972e96f132d2209e475 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/moveaxis_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API moveaxis_intlist { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::moveaxis"; + static constexpr const char* overload_name = "intlist"; + static constexpr const char* schema_str = "moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +}; + +struct TORCH_API moveaxis_int { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::moveaxis"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t source, int64_t destination); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t source, int64_t destination); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4584bebc8d8ebf26a13517f8a623badb42bf9ae0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bbea2594c3138d3b1a4b22a98d9ae14c04529d59 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d1ac11224ac580d337b8e356e2fdf8ca22390cb6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_mse_loss : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c21f17eaee5c12646779c857df5137098ec8b6dc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_mse_loss_out : public at::meta::structured_mse_loss { +void impl(const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/msort_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/msort_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9e1139bd9acad7d084e0ef8bf21d3ade91393c0d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/msort_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor msort(const at::Tensor & self); +TORCH_API at::Tensor & msort_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mul_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..881ca1495c6cbae618af8d75f76a866ea668d4be --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mul_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mul_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "mul.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API mul__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "mul_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API mul_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API mul_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "mul.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API mul__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "mul_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API mul_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..266f7f1e257054b994d4bb2d95684cf0c7be16c7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss_out::call(self, target, p, margin, weight, reduction, out); +} +// aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out) { + return at::_ops::multi_margin_loss_out::call(self, target, p, margin, weight, reduction, out); +} + +// aten::multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor +inline at::Tensor multi_margin_loss(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss::call(self, target, p, margin, weight, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..569dbe7a9092b4533a08e55777c29fb4855bb8e3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API multi_margin_loss_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const ::std::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multi_margin_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); +}; + +struct TORCH_API multi_margin_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multi_margin_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a69230573be1432b645a84633b568748d1b88c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a903e11f66b5159099f50633fb789810ef92d31c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4f1cfa39b9d0afdd5bcf4dd96a6365ebfafd8e2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor multilabel_margin_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multilabel_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multilabel_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multiply_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multiply_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82775810c09aa3e8051265f0b839141b399fffb7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multiply_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor multiply(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & multiply_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & multiply_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor multiply(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & multiply_(at::Tensor & self, const at::Scalar & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow.h new file mode 100644 index 0000000000000000000000000000000000000000..8946a97975a1f657da5d9a52783280ebb029de15 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow.h @@ -0,0 +1,75 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) +inline at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow::call(self, dim, start, length); + } +} + +// aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) +inline at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow::call(self, dim, start, length); + } +} + +// aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) +inline at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); + } +} + +// aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) +inline at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bf6f660379ea8fa2cd49da52ad642f425cd83bfe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d4e3273485581aed6bfd2cebb71b711395112129 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_copy_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor narrow_copy_dense_cpu(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor & narrow_copy_dense_cpu_out(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out); +TORCH_API at::Tensor narrow_copy_sparse(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_copy_dense_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_native.h new file mode 100644 index 0000000000000000000000000000000000000000..46d567c63671d87d24ca2b8c00a21bdb0da2f34a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow_nested_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow_tensor_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fbb064726cc38b64e0547ef51525f555cc9ca732 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc0a4395d1799186f4af12ff02815ea5256570a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple native_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_channel_shuffle_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_channel_shuffle_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..272c077601f5ce9b50ebdb398ae76bab6f1d9077 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_channel_shuffle_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor native_channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor native_channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..f0a27e0db0a159ba6aeb4499b27f4883a74eed2e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor) +inline ::std::tuple native_dropout(const at::Tensor & input, double p, ::std::optional train) { + return at::_ops::native_dropout::call(input, p, train); +} + +// aten::native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple native_dropout_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, double p, ::std::optional train) { + return at::_ops::native_dropout_out::call(input, p, train, out0, out1); +} +// aten::native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple native_dropout_outf(const at::Tensor & input, double p, ::std::optional train, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::native_dropout_out::call(input, p, train, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..66efd8e39cd4581dea580fdb182da5e3686d7447 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor native_dropout_backward(const at::Tensor & grad_output, const at::Tensor & mask, double scale); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8f56f12bebb06eaf569adb13f6f50495c4873182 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple math_group_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps); +TORCH_API ::std::tuple native_group_norm_out_symint(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple native_group_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..936c1d2dd8ed6dbe59349daea79fdeffc5888a5f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API native_group_norm { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, c10::SymInt, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_group_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_group_norm(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps); +}; + +struct TORCH_API native_group_norm_out { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, c10::SymInt, int64_t, double, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_group_norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_group_norm.out(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..66a1e0fa0fa3986968b06ae2f65af9ff5ae46399 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple native_layer_norm_backward_out_symint(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple layer_norm_backward_cpu(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask); +TORCH_API ::std::tuple layer_norm_backward_cuda(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask); +TORCH_API ::std::tuple layer_norm_backward_nested(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..803c442144d231099ef3abb4af3a5850a06311a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API native_layer_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_layer_norm_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask); +}; + +struct TORCH_API native_layer_norm_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_layer_norm_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..728689d5dfed6f4979d479064aaaf06c4ad10bec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple native_layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_symint(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..84746cd44549a68d5122f1b297d50b247647fedd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple native_layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_symint(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..08c49417f494a87d33b943cb305d9c5339ebbc9e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API native_layer_norm { + using schema = ::std::tuple (const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, const ::std::optional &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_layer_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight, Tensor? bias, float eps) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +}; + +struct TORCH_API native_layer_norm_out { + using schema = ::std::tuple (const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, const ::std::optional &, double, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_layer_norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_layer_norm.out(Tensor input, SymInt[] normalized_shape, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_norm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..22746c258d7705a2e5c23aa935c0ae5448554e7b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_norm.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_norm(Tensor self, Scalar p=2) -> Tensor +inline at::Tensor native_norm(const at::Tensor & self, const at::Scalar & p=2) { + return at::_ops::native_norm::call(self, p); +} + +// aten::native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor +inline at::Tensor native_norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype) { + return at::_ops::native_norm_ScalarOpt_dim_dtype::call(self, p, dim, keepdim, dtype); +} + +// aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & p=2) { + return at::_ops::native_norm_out::call(self, p, out); +} +// aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_outf(const at::Tensor & self, const at::Scalar & p, at::Tensor & out) { + return at::_ops::native_norm_out::call(self, p, out); +} + +// aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype) { + return at::_ops::native_norm_ScalarOpt_dim_dtype_out::call(self, p, dim, keepdim, dtype, out); +} +// aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::native_norm_ScalarOpt_dim_dtype_out::call(self, p, dim, keepdim, dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ne_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ne_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..65930b64f36629d6282628bd0697b5bec551bc65 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ne_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor ne(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ne_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor ne(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ne_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..7fb57f77dc98b5232de4758552649b76afda5fda --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_neg : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a5f23a4ec9a0f1387d50ec3c9eecea453ee1d556 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_native.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_neg_out : public at::meta::structured_neg { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_neg(const at::Tensor & self); +TORCH_API at::Tensor & NestedTensor_neg_(at::Tensor & self); +TORCH_API at::Tensor neg_sparse(const at::Tensor & self); +TORCH_API at::Tensor & neg_out_sparse(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & neg_sparse_(at::Tensor & self); +TORCH_API at::Tensor neg_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & neg_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & neg_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/negative_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/negative_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ac45f952b0b5c26debf807ef8620f3c8c32572c0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/negative_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor negative(const at::Tensor & self); +TORCH_API at::Tensor & negative_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & negative_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & negative_(at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6a9590b77ca2fbbc2e52e66c931106ebba61b8d1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor nested_to_padded_tensor(const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_zeros.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_zeros.h new file mode 100644 index 0000000000000000000000000000000000000000..c2734b3f39712e2641a9cf44a702817722bcb034 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_zeros.h @@ -0,0 +1,103 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +namespace symint { + template >> + at::Tensor new_zeros(const at::Tensor & self, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::new_zeros::call(self, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +namespace symint { + template >> + at::Tensor new_zeros(const at::Tensor & self, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::new_zeros::call(self, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +namespace symint { + template >> + at::Tensor new_zeros(const at::Tensor & self, c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::new_zeros::call(self, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +namespace symint { + template >> + at::Tensor new_zeros(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::new_zeros::call(self, size, dtype, layout, device, pin_memory); + } +} + +// aten::new_zeros.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_zeros_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::new_zeros_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & new_zeros_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::new_zeros_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::new_zeros.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_zeros_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::new_zeros_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & new_zeros_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::new_zeros_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::new_zeros.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_zeros_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::new_zeros_out::call(self, size, out); +} +namespace symint { + template >> + at::Tensor & new_zeros_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::new_zeros_out::call(self, size, out); + } +} + +// aten::new_zeros.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_zeros_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::new_zeros_out::call(self, size, out); +} +namespace symint { + template >> + at::Tensor & new_zeros_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::new_zeros_out::call(self, size, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..08055a5de100f6ac96609544071349cd80e8ab90 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor nextafter(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & nextafter_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1dc0e6459b1fb5759de9d818b4944454a7293972 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_nextafter_out : public at::meta::structured_nextafter { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c6a220a4a86dcaa2e9c6371805076891255abb87 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nll_loss2d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss2d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); +}; + +struct TORCH_API nll_loss2d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss2d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44ba2f33d73b49e7c09b25a579a976f12f6a7a40 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple nll_loss2d_forward(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_out(at::Tensor & output, at::Tensor & total_weight, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, at::Tensor & output, at::Tensor & total_weight); +TORCH_API ::std::tuple nll_loss2d_forward_symint_out(at::Tensor & output, at::Tensor & total_weight, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_symint_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & output, at::Tensor & total_weight); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..22cd42969f88e7c3f323987eedd48ba69bac8011 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor nll_loss_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); +TORCH_API at::Tensor & nll_loss_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor & nll_loss_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..12dc14b58fa68fb98eb3a7fb71fa8dc524706864 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_nll_loss_forward_out_cpu : public at::meta::structured_nll_loss_forward { +void impl(const at::Tensor & self, const at::Tensor & target, at::OptionalTensorRef weight, int64_t reduction, int64_t ignore_index, const at::Tensor & output, const at::Tensor & total_weight); +}; +struct TORCH_API structured_nll_loss_forward_out_cuda : public at::meta::structured_nll_loss_forward { +void impl(const at::Tensor & self, const at::Tensor & target, at::OptionalTensorRef weight, int64_t reduction, int64_t ignore_index, const at::Tensor & output, const at::Tensor & total_weight); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9b471adfd91ad07dfb247d886503ce67eca74436 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nll_loss_forward_output { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss_forward"; + static constexpr const char* overload_name = "output"; + static constexpr const char* schema_str = "nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & output, at::Tensor & total_weight); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & output, at::Tensor & total_weight); +}; + +struct TORCH_API nll_loss_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..35cff1f22c5a7bc14e3b1fa2e5da76932328eb3b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor norm(const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor norm(const at::Tensor & self, const at::Scalar & p=2); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & p=2); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const at::Scalar & p, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..848d5cd1809833db7b0cdf6605c51cd0a8632682 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c61ff79b5cb427c7f1c208420a88778c382f13c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_ops.h @@ -0,0 +1,144 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API normal_ { + using schema = at::Tensor & (at::Tensor &, double, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "normal_(Tensor(a!) self, float mean=0, float std=1, *, Generator? generator=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, double mean, double std, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double mean, double std, ::std::optional generator); +}; + +struct TORCH_API normal_functional { + using schema = at::Tensor (const at::Tensor &, double, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal_functional"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "normal_functional(Tensor self, float mean=0, float std=1, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, double mean, double std, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double mean, double std, ::std::optional generator); +}; + +struct TORCH_API normal_Tensor_float_out { + using schema = at::Tensor & (const at::Tensor &, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "Tensor_float_out"; + static constexpr const char* schema_str = "normal.Tensor_float_out(Tensor mean, float std=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & mean, double std, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mean, double std, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API normal_Tensor_float { + using schema = at::Tensor (const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "Tensor_float"; + static constexpr const char* schema_str = "normal.Tensor_float(Tensor mean, float std=1, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & mean, double std, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mean, double std, ::std::optional generator); +}; + +struct TORCH_API normal_float_Tensor_out { + using schema = at::Tensor & (double, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "float_Tensor_out"; + static constexpr const char* schema_str = "normal.float_Tensor_out(float mean, Tensor std, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(double mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, double mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API normal_float_Tensor { + using schema = at::Tensor (double, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "float_Tensor"; + static constexpr const char* schema_str = "normal.float_Tensor(float mean, Tensor std, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(double mean, const at::Tensor & std, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, double mean, const at::Tensor & std, ::std::optional generator); +}; + +struct TORCH_API normal_Tensor_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "Tensor_Tensor_out"; + static constexpr const char* schema_str = "normal.Tensor_Tensor_out(Tensor mean, Tensor std, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API normal_Tensor_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "Tensor_Tensor"; + static constexpr const char* schema_str = "normal.Tensor_Tensor(Tensor mean, Tensor std, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mean, const at::Tensor & std, ::std::optional generator); +}; + +struct TORCH_API normal_float_float { + using schema = at::Tensor (double, double, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "float_float"; + static constexpr const char* schema_str = "normal.float_float(float mean, float std, SymInt[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(double mean, double std, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, double mean, double std, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API normal_float_float_out { + using schema = at::Tensor & (double, double, c10::SymIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "float_float_out"; + static constexpr const char* schema_str = "normal.float_float_out(float mean, float std, SymInt[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(double mean, double std, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, double mean, double std, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API normal_out { + using schema = at::Tensor & (const at::Tensor &, double, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::normal"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "normal.out(Tensor self, float mean=0, float std=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double mean, double std, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double mean, double std, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/not_equal.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/not_equal.h new file mode 100644 index 0000000000000000000000000000000000000000..b76280a22cf9258ab1a7c324f1b5f9f2a8a09263 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/not_equal.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::not_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & not_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::not_equal_Scalar_out::call(self, other, out); +} +// aten::not_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & not_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::not_equal_Scalar_out::call(self, other, out); +} + +// aten::not_equal.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor not_equal(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::not_equal_Scalar::call(self, other); +} + +// aten::not_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & not_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::not_equal_Tensor_out::call(self, other, out); +} +// aten::not_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & not_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::not_equal_Tensor_out::call(self, other, out); +} + +// aten::not_equal.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor not_equal(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::not_equal_Tensor::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nuclear_norm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nuclear_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a6b34de160fde43923f41f9a5e7e8e25919d166c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nuclear_norm_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nuclear_norm { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nuclear_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nuclear_norm(Tensor self, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool keepdim); +}; + +struct TORCH_API nuclear_norm_out { + using schema = at::Tensor & (const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nuclear_norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API nuclear_norm_dim { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nuclear_norm"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "nuclear_norm.dim(Tensor self, int[2] dim, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim); +}; + +struct TORCH_API nuclear_norm_dim_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nuclear_norm"; + static constexpr const char* overload_name = "dim_out"; + static constexpr const char* schema_str = "nuclear_norm.dim_out(Tensor self, int[2] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_like_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_like_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..647998ecceb6687e60b8be1603da28b25563e60a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_like_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor ones_like(const at::Tensor & self, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor ones_like(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +TORCH_API at::Tensor & ones_like_out(at::Tensor & out, const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & ones_like_outf(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e4a8c1b835167eb26bcebf64fa6f173694e4014d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor ones(at::IntArrayRef size, ::std::optional names, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & ones_names_out(at::IntArrayRef size, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor ones(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & ones_out(at::IntArrayRef size, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/output_nr_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/output_nr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..929fe45bd2d036fac48ce62717b2580eece3d60b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/output_nr_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API output_nr { + using schema = int64_t (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::output_nr"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "output_nr(Tensor self) -> int"; + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9fff4b61bf4a0e48d2e928ae3484ac754a814b11 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor pad_symint(const at::Tensor & self, c10::SymIntArrayRef pad, c10::string_view mode="constant", ::std::optional value=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_sequence_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_sequence_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2daf30c26a82433de871943c16cfbf3ba6c4a02c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_sequence_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor pad_sequence(at::TensorList sequences, bool batch_first=false, double padding_value=0.0, c10::string_view padding_side="right"); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_sequence_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_sequence_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5028772632c6127bf77919c74ab90d5d5f3529b2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_sequence_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API pad_sequence { + using schema = at::Tensor (at::TensorList, bool, double, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::pad_sequence"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "pad_sequence(Tensor[] sequences, bool batch_first=False, float padding_value=0.0, str padding_side=\"right\") -> Tensor"; + static at::Tensor call(at::TensorList sequences, bool batch_first, double padding_value, c10::string_view padding_side); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList sequences, bool batch_first, double padding_value, c10::string_view padding_side); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance.h new file mode 100644 index 0000000000000000000000000000000000000000..856ea674243da5c322ef6878d26099654b322272 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::pairwise_distance(Tensor x1, Tensor x2, float p=2, float eps=1e-06, bool keepdim=False) -> Tensor +inline at::Tensor pairwise_distance(const at::Tensor & x1, const at::Tensor & x2, double p=2, double eps=1e-06, bool keepdim=false) { + return at::_ops::pairwise_distance::call(x1, x2, p, eps, keepdim); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..42fad00d396acd3111f738fff081101d89050924 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API pairwise_distance { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::pairwise_distance"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "pairwise_distance(Tensor x1, Tensor x2, float p=2, float eps=1e-06, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2, double p, double eps, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, double eps, bool keepdim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pin_memory_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pin_memory_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b88e1d51e361c9c2efae03ce6310d56b532dcddd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pin_memory_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor pin_memory(const at::Tensor & self, ::std::optional device=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_shuffle.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_shuffle.h new file mode 100644 index 0000000000000000000000000000000000000000..b10009bb2594e43389be17ae319a2e144ba1e4b7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_shuffle.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::pixel_shuffle(Tensor self, int upscale_factor) -> Tensor +inline at::Tensor pixel_shuffle(const at::Tensor & self, int64_t upscale_factor) { + return at::_ops::pixel_shuffle::call(self, upscale_factor); +} + +// aten::pixel_shuffle.out(Tensor self, int upscale_factor, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & pixel_shuffle_out(at::Tensor & out, const at::Tensor & self, int64_t upscale_factor) { + return at::_ops::pixel_shuffle_out::call(self, upscale_factor, out); +} +// aten::pixel_shuffle.out(Tensor self, int upscale_factor, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & pixel_shuffle_outf(const at::Tensor & self, int64_t upscale_factor, at::Tensor & out) { + return at::_ops::pixel_shuffle_out::call(self, upscale_factor, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7b0b300797fd8065d55d2986a571997aa9723cd1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor pixel_unshuffle(const at::Tensor & self, int64_t downscale_factor); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0c4d0ee9842f4dd5b8be495eb8ee2cb9330b8a9b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & pixel_unshuffle_out(const at::Tensor & self, int64_t downscale_factor, at::Tensor & out); +TORCH_API at::Tensor pixel_unshuffle_cpu(const at::Tensor & self, int64_t downscale_factor); +TORCH_API at::Tensor math_pixel_unshuffle(const at::Tensor & self, int64_t downscale_factor); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5519e52dc4a77d3dbb1381fbf0e504b902c50c0e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor poisson(const at::Tensor & self, ::std::optional generator=::std::nullopt); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ca72bbc499cbe771b34828b52be1ff2c1e41740 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor poisson(const at::Tensor & self, ::std::optional generator=::std::nullopt); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_nll_loss.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_nll_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..446693d45d1610ce090d06ddcad1606c983d8a06 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_nll_loss.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::poisson_nll_loss(Tensor input, Tensor target, bool log_input, bool full, float eps, int reduction) -> Tensor +inline at::Tensor poisson_nll_loss(const at::Tensor & input, const at::Tensor & target, bool log_input, bool full, double eps, int64_t reduction) { + return at::_ops::poisson_nll_loss::call(input, target, log_input, full, eps, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37a2b651dcecb1d62c13a967bb687111761fd626 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor polygamma(int64_t n, const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b2c42553902e093ab19341209b3dbbc0b4ae2c74 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & prod_out(at::Tensor & out, const at::Tensor & self, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & prod_outf(const at::Tensor & self, ::std::optional dtype, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..55392443adda6d19f26387b882c59c5e9ae02ddc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor prod(const at::Tensor & self, int64_t dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..23745917adcc69b2ee4d461cd557211c137330b7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor put(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); +TORCH_API at::Tensor & put_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); +TORCH_API at::Tensor & put_outf(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..537d3df2bdca447b9f2b2d259225084ed777cb15 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & put_(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_native.h new file mode 100644 index 0000000000000000000000000000000000000000..30f003f40941e5fe1ef643dfbf6a94cec7a93929 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor put(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); +TORCH_API at::Tensor & put_out(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out); +TORCH_API at::Tensor & put_(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b8823b5ae28af32347e27e7c0e5a036924e7ae70 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/put_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API put_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::put_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "put_(Tensor(a!) self, Tensor index, Tensor source, bool accumulate=False) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate); +}; + +struct TORCH_API put { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::put"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "put(Tensor self, Tensor index, Tensor source, bool accumulate=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate); +}; + +struct TORCH_API put_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::put"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_scale.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_scale.h new file mode 100644 index 0000000000000000000000000000000000000000..8be4feb48832dc0c9a8d632c8d789705ec37bbe3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_scale.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::q_scale(Tensor self) -> float +inline double q_scale(const at::Tensor & self) { + return at::_ops::q_scale::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cdd41befdf26b326f3cad9a1ac5a24ab3baa952a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & quantize_per_tensor_dynamic_out(at::Tensor & out, const at::Tensor & self, at::ScalarType dtype, bool reduce_range); +TORCH_API at::Tensor & quantize_per_tensor_dynamic_outf(const at::Tensor & self, at::ScalarType dtype, bool reduce_range, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..601c66d636e47a4d99423b95403dbe5014c63fa0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API quantize_per_tensor { + using schema = at::Tensor (const at::Tensor &, double, int64_t, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantize_per_tensor"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_tensor_tensor_qparams { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantize_per_tensor"; + static constexpr const char* overload_name = "tensor_qparams"; + static constexpr const char* schema_str = "quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_tensor_tensors { + using schema = ::std::vector (at::TensorList, const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantize_per_tensor"; + static constexpr const char* overload_name = "tensors"; + static constexpr const char* schema_str = "quantize_per_tensor.tensors(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype) -> Tensor[]"; + static ::std::vector call(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_tensor_out { + using schema = at::Tensor & (const at::Tensor &, double, int64_t, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantize_per_tensor"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "quantize_per_tensor.out(Tensor self, float scale, int zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API quantize_per_tensor_tensor_qparams_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantize_per_tensor"; + static constexpr const char* overload_name = "tensor_qparams_out"; + static constexpr const char* schema_str = "quantize_per_tensor.tensor_qparams_out(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API quantize_per_tensor_tensors_out { + using schema = void (at::TensorList, const at::Tensor &, const at::Tensor &, at::ScalarType, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantize_per_tensor"; + static constexpr const char* overload_name = "tensors_out"; + static constexpr const char* schema_str = "quantize_per_tensor.tensors_out(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_gru_cell_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_gru_cell_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..460a9ab189abf623bcb8fd3c96153c8e38ddfcf8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_gru_cell_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor quantized_gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_lstm_cell_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_lstm_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..59699994c504b8a1cbacefaed59175c8b6c9605b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_lstm_cell_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple quantized_lstm_cell(const at::Tensor & input, at::TensorList hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool3d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..900001679b13173fdefcb9062de971dbda81d37b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool3d_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & quantized_max_pool3d_out(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API at::Tensor quantized_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a4a57425bd04ff3a56d15705093eb9a5b89a101a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API quantized_rnn_tanh_cell { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantized_rnn_tanh_cell"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "quantized_rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rad2deg_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rad2deg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6e02a1d86889a70a1560e8ab0e174528f08df92b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rad2deg_native.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor rad2deg(const at::Tensor & self); +TORCH_API at::Tensor & rad2deg_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rad2deg_(at::Tensor & self); +TORCH_API at::Tensor rad2deg_sparse(const at::Tensor & self); +TORCH_API at::Tensor & rad2deg_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rad2deg_sparse_(at::Tensor & self); +TORCH_API at::Tensor rad2deg_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & rad2deg_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rad2deg_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rad2deg_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rad2deg_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4d263ceda5a10579a1b4551fdf562377837481e3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rad2deg_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API rad2deg { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rad2deg"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rad2deg(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API rad2deg_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rad2deg_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rad2deg_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API rad2deg_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rad2deg"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "rad2deg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..acf3e52a2d9715162468b34dc0cd202159de53fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rand_like_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rand_like_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9f75ffe2779e54c4e6c49bb87e6254b387874204 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rand_like_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API rand_like { + using schema = at::Tensor (const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rand_like"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rand_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API rand_like_generator { + using schema = at::Tensor (const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rand_like"; + static constexpr const char* overload_name = "generator"; + static constexpr const char* schema_str = "rand_like.generator(Tensor self, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API rand_like_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rand_like"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "rand_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +}; + +struct TORCH_API rand_like_generator_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rand_like"; + static constexpr const char* overload_name = "generator_out"; + static constexpr const char* schema_str = "rand_like.generator_out(Tensor self, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional generator, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator, ::std::optional memory_format, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cfc441b9292c522c383dfea7f2284855ac25e208 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_compositeexplicitautograd_dispatch.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size); +TORCH_API at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size); +TORCH_API at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_like.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_like.h new file mode 100644 index 0000000000000000000000000000000000000000..c07fa132b3f08a8307a4c4fc605166d3b322c8c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_like.h @@ -0,0 +1,419 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.generator(Tensor self, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator::call(self, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator::call(self, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.generator(Tensor self, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_generator::call(self, high, generator, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_generator::call(self, high, generator, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.generator(Tensor self, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator::call(self, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator::call(self, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.generator(Tensor self, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_generator::call(self, high, generator, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_generator::call(self, high, generator, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.Tensor(Tensor self, Tensor high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, const at::Tensor & high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_Tensor::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +// aten::randint_like.Tensor(Tensor self, Tensor high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, const at::Tensor & high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_Tensor::call(self, high, dtype, layout, device, pin_memory, memory_format); +} + +// aten::randint_like.Tensor_generator(Tensor self, Tensor high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, const at::Tensor & high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_Tensor_generator::call(self, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +// aten::randint_like.Tensor_generator(Tensor self, Tensor high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, const at::Tensor & high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_Tensor_generator::call(self, high, generator, dtype, layout, device, pin_memory, memory_format); +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt low, c10::SymInt high, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.low_generator_dtype(Tensor self, SymInt low, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.low_generator_dtype(Tensor self, SymInt low, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.low_generator_dtype(Tensor self, SymInt low, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.low_generator_dtype(Tensor self, SymInt low, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::randint_like_low_generator_dtype::call(self, low, high, generator, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, int64_t high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, int64_t high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, c10::SymInt high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_outf(const at::Tensor & self, c10::SymInt high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, c10::SymInt high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.generator_out(Tensor self, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); + } +} + +// aten::randint_like.generator_out(Tensor self, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); + } +} + +// aten::randint_like.generator_out(Tensor self, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); + } +} + +// aten::randint_like.generator_out(Tensor self, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_outf(const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_generator_out::call(self, high, generator, memory_format, out); + } +} + +// aten::randint_like.Tensor_out(Tensor self, Tensor high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_Tensor_out::call(self, high, memory_format, out); +} +// aten::randint_like.Tensor_out(Tensor self, Tensor high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, const at::Tensor & high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_Tensor_out::call(self, high, memory_format, out); +} + +// aten::randint_like.Tensor_generator_out(Tensor self, Tensor high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_Tensor_generator_out::call(self, high, generator, memory_format, out); +} +// aten::randint_like.Tensor_generator_out(Tensor self, Tensor high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, const at::Tensor & high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_Tensor_generator_out::call(self, high, generator, memory_format, out); +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t low, int64_t high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t low, int64_t high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, int64_t low, int64_t high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, int64_t low, int64_t high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_outf(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_generator_dtype_out(Tensor self, SymInt low, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); + } +} + +// aten::randint_like.low_generator_dtype_out(Tensor self, SymInt low, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); + } +} + +// aten::randint_like.low_generator_dtype_out(Tensor self, SymInt low, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional memory_format=::std::nullopt) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); + } +} + +// aten::randint_like.low_generator_dtype_out(Tensor self, SymInt low, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_outf(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); +} +namespace symint { + template >> + at::Tensor & randint_like_outf(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_generator_dtype_out::call(self, low, high, generator, memory_format, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_like_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_like_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f0098e8783074a289d5b170f089a96b0b2a62f9d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_like_native.h @@ -0,0 +1,37 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randint_like_out_symint(const at::Tensor & self, c10::SymInt high, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor randint_like(const at::Tensor & self, int64_t high, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randint_like_generator_out_symint(const at::Tensor & self, c10::SymInt high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor randint_like(const at::Tensor & self, const at::Tensor & high, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randint_like_Tensor_out(const at::Tensor & self, const at::Tensor & high, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor randint_like(const at::Tensor & self, const at::Tensor & high, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randint_like_Tensor_generator_out(const at::Tensor & self, const at::Tensor & high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randint_like_low_dtype_out_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randint_like_low_generator_dtype_out_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, ::std::optional generator, ::std::optional memory_format, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_native.h new file mode 100644 index 0000000000000000000000000000000000000000..be7ecaa2025b98faa52a46b2bfe43728622f99a1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor randn_like(const at::Tensor & self, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randn_like_out(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor randn_like(const at::Tensor & self, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randn_like_generator_out(const at::Tensor & self, ::std::optional generator, ::std::optional memory_format, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..09a116a24bc596fdc4833164b11e441ccf49f91b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_ops.h @@ -0,0 +1,111 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API randn { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_generator { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "generator"; + static constexpr const char* schema_str = "randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_names { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "names"; + static constexpr const char* schema_str = "randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_generator_with_names { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "generator_with_names"; + static constexpr const char* schema_str = "randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_out { + using schema = at::Tensor & (c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, at::Tensor & out); +}; + +struct TORCH_API randn_generator_out { + using schema = at::Tensor & (c10::SymIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "generator_out"; + static constexpr const char* schema_str = "randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API randn_names_out { + using schema = at::Tensor & (c10::SymIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "names_out"; + static constexpr const char* schema_str = "randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out); +}; + +struct TORCH_API randn_generator_with_names_out { + using schema = at::Tensor & (c10::SymIntArrayRef, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randn"; + static constexpr const char* overload_name = "generator_with_names_out"; + static constexpr const char* schema_str = "randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/random_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/random_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ab3fa03ba38cfc4c69e3569a3803651c578b1c3d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/random_compositeexplicitautograd_dispatch.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor random(const at::Tensor & self, int64_t from, ::std::optional to, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_out(at::Tensor & out, const at::Tensor & self, int64_t from, ::std::optional to, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_outf(const at::Tensor & self, int64_t from, ::std::optional to, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor random(const at::Tensor & self, int64_t to, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_out(at::Tensor & out, const at::Tensor & self, int64_t to, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_outf(const at::Tensor & self, int64_t to, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor random(const at::Tensor & self, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_out(at::Tensor & out, const at::Tensor & self, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_outf(const at::Tensor & self, ::std::optional generator, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randperm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randperm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bab479cbf33b99d2083c5fa8977a615ad692cd54 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randperm_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API randperm { + using schema = at::Tensor (c10::SymInt, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randperm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "randperm(SymInt n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randperm_generator { + using schema = at::Tensor (c10::SymInt, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randperm"; + static constexpr const char* overload_name = "generator"; + static constexpr const char* schema_str = "randperm.generator(SymInt n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::SymInt n, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt n, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randperm_out { + using schema = at::Tensor & (c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randperm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "randperm.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymInt n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt n, at::Tensor & out); +}; + +struct TORCH_API randperm_generator_out { + using schema = at::Tensor & (c10::SymInt, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::randperm"; + static constexpr const char* overload_name = "generator_out"; + static constexpr const char* schema_str = "randperm.generator_out(SymInt n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymInt n, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymInt n, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range.h new file mode 100644 index 0000000000000000000000000000000000000000..e2d1f40a832310382fdf5acb71fbb2acd1b5cc7e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1, at::TensorOptions options={}) { + return at::_ops::range_step::call(start, end, step, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::range_step::call(start, end, step, dtype, layout, device, pin_memory); +} + +// aten::range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, at::TensorOptions options={}) { + return at::_ops::range::call(start, end, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::range::call(start, end, dtype, layout, device, pin_memory); +} + +// aten::range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end) { + return at::_ops::range_out_::call(start, end, out); +} +// aten::range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, at::Tensor & out) { + return at::_ops::range_out_::call(start, end, out); +} + +// aten::range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step) { + return at::_ops::range_out::call(start, end, step, out); +} +// aten::range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out) { + return at::_ops::range_out::call(start, end, step, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0012d0c0413488c93cf1f1e3aa3f4229562b211a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step); +TORCH_API at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6dd11b2cfbdf95b6601ed1df9017b14a4cd7ec61 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor ravel(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..439ae73db9b3aa9b14065f7e1584faf3f6ac9a35 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API ravel { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::ravel"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ravel(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/record_stream_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/record_stream_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a8922fa87a7e63c12789b44868ef41077fe7a9d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/record_stream_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void record_stream(at::Tensor & self, at::Stream s); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ac8af1a363d1c9f5db7db43a81d2914109e3d5ea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API reflection_pad1d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::reflection_pad1d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); +}; + +struct TORCH_API reflection_pad1d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::reflection_pad1d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..88de6008e364a83674c442b019d1f36093ec8d9e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_backward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor reflection_pad2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad2d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & reflection_pad2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d17e59fbe477843c687e0c5d17708e5ff819643 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_backward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor reflection_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad3d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & reflection_pad3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2ffe21936b010bf9854ae45a45ce696e794926a7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor reflection_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..47d0aaca9357d924410012f9fecb556c2aab9113 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor reflection_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & reflection_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..48f8dfc7f585bbdea59badc6e04da0ddff4b4411 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor reflection_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & reflection_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu6.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu6.h new file mode 100644 index 0000000000000000000000000000000000000000..39fbd88a629d15b8009bbae87cab0e7eef9d8054 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu6.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::relu6(Tensor self) -> Tensor +inline at::Tensor relu6(const at::Tensor & self) { + return at::_ops::relu6::call(self); +} + +// aten::relu6_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & relu6_(at::Tensor & self) { + return at::_ops::relu6_::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7be4f7bc996fe76403a9e9aa71cb120604516df0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu_native.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & relu_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor relu(const at::Tensor & self); +TORCH_API at::Tensor & relu_(at::Tensor & self); +TORCH_API at::Tensor NestedTensor_relu(const at::Tensor & self); +TORCH_API at::Tensor & NestedTensor_relu_(at::Tensor & self); +TORCH_API at::Tensor relu_sparse(const at::Tensor & self); +TORCH_API at::Tensor & relu_sparse_(at::Tensor & self); +TORCH_API at::Tensor relu_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & relu_sparse_csr_(at::Tensor & self); +TORCH_API at::Tensor mkldnn_relu(const at::Tensor & self); +TORCH_API at::Tensor & mkldnn_relu_(at::Tensor & self); +TORCH_API at::Tensor relu_quantized_cpu(const at::Tensor & self); +TORCH_API at::Tensor & relu_quantized_cpu_(at::Tensor & self); +TORCH_API at::Tensor relu_quantized_cuda(const at::Tensor & self); +TORCH_API at::Tensor & relu_quantized_cuda_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0134ff5907918cfcba9239b34f56301199b2748 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor remainder(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & remainder_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & remainder_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d93cdc99c79c9011e8f83570843daf16d8e69ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor remainder(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & remainder_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rename_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rename_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..40e63700f39bec7ceed4c2596694194bac9fda8d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rename_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API rename_ { + using schema = at::Tensor & (at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rename_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rename_(Tensor(a!) self, Dimname[]? names) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, ::std::optional names); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, ::std::optional names); +}; + +struct TORCH_API rename { + using schema = at::Tensor (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rename"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rename(Tensor(a) self, Dimname[]? names) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, ::std::optional names); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional names); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1fe323549a841c89f619351ee507d998f68b5752 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API repeat { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::repeat"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "repeat(Tensor self, SymInt[] repeats) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef repeats); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef repeats); +}; + +struct TORCH_API repeat_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::repeat"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "repeat.out(Tensor self, SymInt[] repeats, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef repeats, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef repeats, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dbb7258202bcf506208b88bf25f496927fd8e728 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad1d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5dce80519c41cebd68d282550f90ae56249435ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_replication_pad1d_out_cpu : public at::meta::structured_replication_pad1d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +struct TORCH_API structured_replication_pad1d_out_cuda : public at::meta::structured_replication_pad1d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..ed646d2a0c5fc5ac0b37ca05b56a58324094f1f1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_replication_pad2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef padding); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d.h new file mode 100644 index 0000000000000000000000000000000000000000..bdc6da081ecd9fdee5ef417600665922abfcd2ea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad3d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad3d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d_out::call(self, padding, out); +} +namespace symint { + template >> + at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d_out::call(self, padding, out); + } +} + +// aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad3d_out::call(self, padding, out); +} +namespace symint { + template >> + at::Tensor & replication_pad3d_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad3d_out::call(self, padding, out); + } +} + +// aten::replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor +inline at::Tensor replication_pad3d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d::call(self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template >> + at::Tensor replication_pad3d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d::call(self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor +inline at::Tensor replication_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d::call(self, padding); +} +namespace symint { + template >> + at::Tensor replication_pad3d(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d::call(self, padding); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..31d2c9aa0a720f000716e109b3c0afc7fe9bf875 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API replication_pad3d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::replication_pad3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); +}; + +struct TORCH_API replication_pad3d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::replication_pad3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/requires_grad_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/requires_grad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..62b6ae799f9aee983f27d925cd755860b28ec6d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/requires_grad_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API requires_grad_ { + using schema = at::Tensor & (at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::requires_grad_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "requires_grad_(Tensor(a!) self, bool requires_grad=True) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, bool requires_grad); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, bool requires_grad); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d0c8314fc416dda3e5d904bc3b5691c33f5fe65d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor reshape_as(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor reshape_as_nested(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cb11f5de3b51cbd2829867024059c68f35f467d7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API reshape_as { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::reshape_as"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "reshape_as(Tensor(a) self, Tensor other) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2e4a7f6a932530181d815db882ea17b7500769d8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor resize_as_sparse(const at::Tensor & self, const at::Tensor & the_template); +TORCH_API const at::Tensor & resize_as_sparse_out(const at::Tensor & self, const at::Tensor & the_template, const at::Tensor & out); +TORCH_API const at::Tensor & resize_as_sparse_(const at::Tensor & self, const at::Tensor & the_template); +TORCH_API const at::Tensor & resize_as_sparse_compressed_(const at::Tensor & self, const at::Tensor & the_template); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c41bac473746248e1475bc9990ec4adebeeba24a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API resize_as_sparse_ { + using schema = const at::Tensor & (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::resize_as_sparse_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "resize_as_sparse_(Tensor(a!) self, Tensor the_template) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, const at::Tensor & the_template); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & the_template); +}; + +struct TORCH_API resize_as_sparse_out { + using schema = const at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::resize_as_sparse"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "resize_as_sparse.out(Tensor self, Tensor the_template, *, Tensor(a!) out) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, const at::Tensor & the_template, const at::Tensor & out); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & the_template, const at::Tensor & out); +}; + +struct TORCH_API resize_as_sparse { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::resize_as_sparse"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "resize_as_sparse(Tensor self, Tensor the_template) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & the_template); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & the_template); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_conj_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_conj_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ef36ac996710062c0e5b9be66a4d05008562e75b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_conj_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor resolve_conj(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/result_type.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/result_type.h new file mode 100644 index 0000000000000000000000000000000000000000..56a5c023f724d748b3045762ce86c463d6dea1fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/result_type.h @@ -0,0 +1,51 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType +inline at::ScalarType result_type(const at::Tensor & tensor, const at::Tensor & other) { + return at::_ops::result_type_Tensor::call(tensor, other); +} + +// aten::result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType +inline at::ScalarType result_type(const at::Tensor & tensor, const at::Scalar & other) { + return at::_ops::result_type_Scalar::call(tensor, other); +} + +// aten::result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType +inline at::ScalarType result_type(const at::Scalar & scalar, const at::Tensor & tensor) { + return at::_ops::result_type_Scalar_Tensor::call(scalar, tensor); +} + +// aten::result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType +inline at::ScalarType result_type(const at::Scalar & scalar1, const at::Scalar & scalar2) { + return at::_ops::result_type_Scalar_Scalar::call(scalar1, scalar2); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/retain_grad_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/retain_grad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0c25f483028b39fc4185a34f0d35733c8322efc3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/retain_grad_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void retain_grad(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..275e16abee6f130ba145bc7f7f5fb09a943f972d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::rnn_relu.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor) +inline ::std::tuple rnn_relu(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) { + return at::_ops::rnn_relu_input::call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); +} + +// aten::rnn_relu.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor) +inline ::std::tuple rnn_relu(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) { + return at::_ops::rnn_relu_data::call(data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d10e32f7bf80fa24e82617027460468e4a62ace --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple rnn_tanh(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); +TORCH_API ::std::tuple rnn_tanh(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/roll.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/roll.h new file mode 100644 index 0000000000000000000000000000000000000000..c5381172983926e85555d95d43353e604df81f03 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/roll.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::roll(Tensor self, SymInt[1] shifts, int[1] dims=[]) -> Tensor +inline at::Tensor roll(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll::call(self, c10::fromIntArrayRefSlow(shifts), dims); +} +namespace symint { + template >> + at::Tensor roll(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll::call(self, c10::fromIntArrayRefSlow(shifts), dims); + } +} + +// aten::roll(Tensor self, SymInt[1] shifts, int[1] dims=[]) -> Tensor +inline at::Tensor roll_symint(const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll::call(self, shifts, dims); +} +namespace symint { + template >> + at::Tensor roll(const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll::call(self, shifts, dims); + } +} + +// aten::roll.out(Tensor self, SymInt[1] shifts, int[1] dims=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & roll_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll_out::call(self, c10::fromIntArrayRefSlow(shifts), dims, out); +} +namespace symint { + template >> + at::Tensor & roll_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll_out::call(self, c10::fromIntArrayRefSlow(shifts), dims, out); + } +} + +// aten::roll.out(Tensor self, SymInt[1] shifts, int[1] dims=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & roll_outf(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims, at::Tensor & out) { + return at::_ops::roll_out::call(self, c10::fromIntArrayRefSlow(shifts), dims, out); +} +namespace symint { + template >> + at::Tensor & roll_outf(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims, at::Tensor & out) { + return at::_ops::roll_out::call(self, c10::fromIntArrayRefSlow(shifts), dims, out); + } +} + +// aten::roll.out(Tensor self, SymInt[1] shifts, int[1] dims=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & roll_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll_out::call(self, shifts, dims, out); +} +namespace symint { + template >> + at::Tensor & roll_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims={}) { + return at::_ops::roll_out::call(self, shifts, dims, out); + } +} + +// aten::roll.out(Tensor self, SymInt[1] shifts, int[1] dims=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & roll_symint_outf(const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims, at::Tensor & out) { + return at::_ops::roll_out::call(self, shifts, dims, out); +} +namespace symint { + template >> + at::Tensor & roll_outf(const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims, at::Tensor & out) { + return at::_ops::roll_out::call(self, shifts, dims, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a14878f4f7c3106029d416a3e4bb68267788c482 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & row_indices_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & row_indices_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..25f2f1890b3b19883eeae9fdd8cdb56474038649 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor row_indices_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..171e4bde6e657894ce7a30a4f321703f1d42ddf6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_indices_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API row_indices { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::row_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "row_indices(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f711e2cd74fbb5c686f48ab98cf4ab2a9f359ef1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor row_stack(at::TensorList tensors); +TORCH_API at::Tensor & row_stack_out(at::Tensor & out, at::TensorList tensors); +TORCH_API at::Tensor & row_stack_outf(at::TensorList tensors, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9da0653ccb336d9caddf60ab49dcca970648a23b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor row_stack(at::TensorList tensors); +TORCH_API at::Tensor & row_stack_out(at::TensorList tensors, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39a30355cb2625e44d18ac4ace7ef4db5992e8b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor rrelu_with_noise_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result); +TORCH_API at::Tensor & rrelu_with_noise_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result); +TORCH_API at::Tensor & rrelu_with_noise_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2c57f1b5dcfef081ee825fbb33d9b735c760c5af --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API rsqrt { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rsqrt"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rsqrt(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API rsqrt_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rsqrt_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rsqrt_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API rsqrt_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rsqrt"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "rsqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsub_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsub_native.h new file mode 100644 index 0000000000000000000000000000000000000000..084a55157a4316b45b0af72e32895026fd0ab5c7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsub_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & rsub_Tensor_out(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor rsub(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor rsub(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & rsub_Scalar_out(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scaled_dot_product_attention.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scaled_dot_product_attention.h new file mode 100644 index 0000000000000000000000000000000000000000..5dabbc6a65a867bd952f67eaaa766425dbec614b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scaled_dot_product_attention.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None, bool enable_gqa=False) -> Tensor +inline at::Tensor scaled_dot_product_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false) { + return at::_ops::scaled_dot_product_attention::call(query, key, value, attn_mask, dropout_p, is_causal, scale, enable_gqa); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da125dc4de2953f415bde4577cb8bd06548b5028 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor scatter_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); +TORCH_API at::Tensor & scatter_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..386ac3678e461508269a75451b14428a929af5e6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_cpu_dispatch.h @@ -0,0 +1,43 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_reduce_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_reduce_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be06f5829f85bc2a0446c26e7eb425e5dac41f14 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_reduce_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor scatter_reduce(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self=true); +TORCH_API at::Tensor & scatter_reduce_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self=true); +TORCH_API at::Tensor & scatter_reduce_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self, at::Tensor & out); +TORCH_API at::Tensor & scatter_reduce_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self=true); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/searchsorted_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/searchsorted_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5d7f31da8cd46fbd4b4f55a459321e4f338d650 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/searchsorted_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); +TORCH_API at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8f2d0f0cc72cf825bd45d663b0500211d09e00b8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor select_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index); +TORCH_API at::Tensor select_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_scatter_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_scatter_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..78d7239953be25c9b4a7df113c6b8da28069fc67 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_scatter_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & select_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index); +TORCH_API at::Tensor & select_scatter_outf(const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index, at::Tensor & out); +TORCH_API at::Tensor & select_scatter_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index); +TORCH_API at::Tensor & select_scatter_symint_outf(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_data_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..781c53df6fdb4fbe78bc92f56d796cf9c6466e2d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_data_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void set_data(at::Tensor & self, const at::Tensor & new_data); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_data_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_data_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d827388d4de650777ec8dfb7a0d03f21ed883d05 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_data_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API set_data { + using schema = void (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::set_data"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "set_data(Tensor(a!) self, Tensor new_data) -> ()"; + static void call(at::Tensor & self, const at::Tensor & new_data); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & new_data); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ecda237baf44815149aecc31a8bb4316fbf21902 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_native.h @@ -0,0 +1,43 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor set(const at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_source_Storage_out(const at::Tensor & self, at::Storage source, at::Tensor & out); +TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source); +TORCH_API at::Tensor set_symint(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_source_Storage_storage_offset_out_symint(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor & set_storage_cpu_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set_storage_cuda_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set_storage_meta__symint(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_storage_quantized_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set__symint(at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor set(const at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_source_Tensor_out(const at::Tensor & self, const at::Tensor & source, at::Tensor & out); +TORCH_API at::Tensor & set_tensor_(at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor set(const at::Tensor & self); +TORCH_API at::Tensor & set_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & set_cpu_(at::Tensor & self); +TORCH_API at::Tensor & set_cuda_(at::Tensor & self); +TORCH_API at::Tensor & set_meta_(at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5818786f4a80b6a6c9fada200b87438cf9a1cb6e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_sigmoid_backward : public TensorIteratorBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & output); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..74f4e4aa25f333e542c60f160eb6a765dad787e8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sigmoid_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sigmoid_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "sigmoid_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); +}; + +struct TORCH_API sigmoid_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sigmoid_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sigmoid_backward(Tensor grad_output, Tensor output) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & output); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit.h new file mode 100644 index 0000000000000000000000000000000000000000..16a58fd557a7802cc83e25b04e991ca9f8fd5c3c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::signbit(Tensor self) -> Tensor +inline at::Tensor signbit(const at::Tensor & self) { + return at::_ops::signbit::call(self); +} + +// aten::signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & signbit_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::signbit_out::call(self, out); +} +// aten::signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & signbit_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::signbit_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8de281ae8f0ae305c60e182328921a27ac1f57f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor signbit(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..08f0a18bfd959a12ff2a31738205fb63d98dcaa2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API signbit { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::signbit"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "signbit(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API signbit_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::signbit"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..66791315aa9a0757c9aeb8838c0188dbbd6baad7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor silu(const at::Tensor & self); +TORCH_API at::Tensor & silu_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & silu_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & silu_(at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..045a16620389587c4fa166b8b1dfc66e9361907b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API silu { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::silu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "silu(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API silu_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::silu_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "silu_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API silu_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::silu"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "silu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sin_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..62d1c634bf47293125583b913fd9edf96bbfa316 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sin_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sin { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sin(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API sin_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sin_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sin_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API sin_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..de99368d652ec3bb48cce605993ff8c5ae4f5d73 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor sinc(const at::Tensor & self); +TORCH_API at::Tensor & sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinc_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh.h new file mode 100644 index 0000000000000000000000000000000000000000..fcdebf78e2de9684fe3e818120bf94956452f845 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sinh(Tensor self) -> Tensor +inline at::Tensor sinh(const at::Tensor & self) { + return at::_ops::sinh::call(self); +} + +// aten::sinh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & sinh_(at::Tensor & self) { + return at::_ops::sinh_::call(self); +} + +// aten::sinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sinh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::sinh_out::call(self, out); +} +// aten::sinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sinh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::sinh_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice.h new file mode 100644 index 0000000000000000000000000000000000000000..f6a3da46b38aee34578f0771652c84b4dce5774e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a) +inline at::Tensor slice(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1) { + return at::_ops::slice_Tensor::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step); +} +namespace symint { + template >> + at::Tensor slice(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1) { + return at::_ops::slice_Tensor::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step); + } +} + +// aten::slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a) +inline at::Tensor slice_symint(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1) { + return at::_ops::slice_Tensor::call(self, dim, start, end, step); +} +namespace symint { + template >> + at::Tensor slice(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1) { + return at::_ops::slice_Tensor::call(self, dim, start, end, step); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..29caaa426c470b0004bcea24673ffb384eb97ac7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor +inline at::Tensor slice_copy(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1) { + return at::_ops::slice_copy_Tensor::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step); +} +namespace symint { + template >> + at::Tensor slice_copy(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1) { + return at::_ops::slice_copy_Tensor::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step); + } +} + +// aten::slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor +inline at::Tensor slice_copy_symint(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1) { + return at::_ops::slice_copy_Tensor::call(self, dim, start, end, step); +} +namespace symint { + template >> + at::Tensor slice_copy(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1) { + return at::_ops::slice_copy_Tensor::call(self, dim, start, end, step); + } +} + +// aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step, out); +} +namespace symint { + template >> + at::Tensor & slice_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step, out); + } +} + +// aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_copy_outf(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, int64_t step, at::Tensor & out) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step, out); +} +namespace symint { + template >> + at::Tensor & slice_copy_outf(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, int64_t step, at::Tensor & out) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start.has_value() ? ::std::make_optional(c10::SymInt(*start)) : ::std::nullopt, end.has_value() ? ::std::make_optional(c10::SymInt(*end)) : ::std::nullopt, step, out); + } +} + +// aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start, end, step, out); +} +namespace symint { + template >> + at::Tensor & slice_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start, end, step, out); + } +} + +// aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_copy_symint_outf(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start, end, step, out); +} +namespace symint { + template >> + at::Tensor & slice_copy_outf(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out) { + return at::_ops::slice_copy_Tensor_out::call(self, dim, start, end, step, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_inverse_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_inverse_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1205cd58fa8bcfb1badac3a46018a23313c854b7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_inverse_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor slice_inverse(const at::Tensor & self, const at::Tensor & src, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1); +TORCH_API at::Tensor slice_inverse_symint(const at::Tensor & self, const at::Tensor & src, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_scatter_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_scatter_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3e02da96a40928c1b60946917690bb66e9870493 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_scatter_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API slice_scatter { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, ::std::optional, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::slice_scatter"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "slice_scatter(Tensor self, Tensor src, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step); +}; + +struct TORCH_API slice_scatter_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, ::std::optional, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::slice_scatter"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "slice_scatter.out(Tensor self, Tensor src, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c9d226a3266a45b0050bfb333495c11e33ef1222 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & slow_conv_dilated3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor & slow_conv_dilated3d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor & slow_conv_dilated3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_dilated3d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..064dae3b1f82af20478232a1a9e2956ef26b8cb2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor slow_conv_dilated3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_dilated3d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e0b87be33a19a60b95fcacac3087398899ebd076 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & slow_conv_dilated3d_out_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor slow_conv_dilated3d_cpu(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_dilated3d_cuda(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d.h new file mode 100644 index 0000000000000000000000000000000000000000..7c34da47d2263429956a372104583c9fb1100450 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_transpose2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template >> + at::Tensor & slow_conv_transpose2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_transpose2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template >> + at::Tensor & slow_conv_transpose2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_transpose2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation, out); +} +namespace symint { + template >> + at::Tensor & slow_conv_transpose2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation, out); + } +} + +// aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_transpose2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation, out); +} +namespace symint { + template >> + at::Tensor & slow_conv_transpose2d_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out) { + return at::_ops::slow_conv_transpose2d_out::call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation, out); + } +} + +// aten::slow_conv_transpose2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, SymInt[2] dilation=1) -> Tensor +inline at::Tensor slow_conv_transpose2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1) { + return at::_ops::slow_conv_transpose2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(dilation)); +} +namespace symint { + template >> + at::Tensor slow_conv_transpose2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1) { + return at::_ops::slow_conv_transpose2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(dilation)); + } +} + +// aten::slow_conv_transpose2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, SymInt[2] dilation=1) -> Tensor +inline at::Tensor slow_conv_transpose2d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)) { + return at::_ops::slow_conv_transpose2d::call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation); +} +namespace symint { + template >> + at::Tensor slow_conv_transpose2d(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)) { + return at::_ops::slow_conv_transpose2d::call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02e8a43dfac4d12c0d87ad2fe3cc5170b61cc9c0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor slow_conv_transpose3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_transpose3d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor & slow_conv_transpose3d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor & slow_conv_transpose3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose3d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smm_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a1848d35a5b2c8bacad47ca50a1ec78a1156bb8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smm_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor smm(const at::Tensor & self, const at::Tensor & mat2); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dd6d37784e8e022002c997cb5c5db0e9041fc8a2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smm_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API smm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::smm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "smm(Tensor self, Tensor mat2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fbf41c9b188f9d18df339a675521d294f378022e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor smooth_l1_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta); +TORCH_API at::Tensor & smooth_l1_loss_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & grad_input); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..684247cc1714fae05ffddd65685d8274a33cd5bc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_smooth_l1_loss_out : public at::meta::structured_smooth_l1_loss { +void impl(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/soft_margin_loss_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/soft_margin_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..d08b18af53a54b7d3a5f93fa2e91d81b36d138a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/soft_margin_loss_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & soft_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::soft_margin_loss_backward_grad_input::call(grad_output, self, target, reduction, grad_input); +} +// aten::soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & soft_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input) { + return at::_ops::soft_margin_loss_backward_grad_input::call(grad_output, self, target, reduction, grad_input); +} + +// aten::soft_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor +inline at::Tensor soft_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::soft_margin_loss_backward::call(grad_output, self, target, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softmax.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softmax.h new file mode 100644 index 0000000000000000000000000000000000000000..b7390843f53213e77c4bed036ca853be5e7cdb49 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softmax.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor +inline at::Tensor softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::softmax_int::call(self, dim, dtype); +} + +// aten::softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::softmax_int_out::call(self, dim, dtype, out); +} +// aten::softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & softmax_outf(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::softmax_int_out::call(self, dim, dtype, out); +} + +// aten::softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::softmax_Dimname::call(self, dim, dtype); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..6888047ba23da2fa9e80978015744e34ea5d6675 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & softplus_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { + return at::_ops::softplus_backward_grad_input::call(grad_output, self, beta, threshold, grad_input); +} +// aten::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & softplus_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & grad_input) { + return at::_ops::softplus_backward_grad_input::call(grad_output, self, beta, threshold, grad_input); +} + +// aten::softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor +inline at::Tensor softplus_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { + return at::_ops::softplus_backward::call(grad_output, self, beta, threshold); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..10e9230947efb1da91827c2eb753fd3f22335f8a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_softplus_backward_out : public at::meta::structured_softplus_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fe59d0b13c37c67d1f96ea2a3482993e0839650f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_softplus_out : public at::meta::structured_softplus { +void impl(const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fe3e190705e94baac05c35e4128463e78c5b53dd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor softshrink_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..437535729ad6e9cc3cef63023ee1f444d8f8aa74 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor softshrink_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); +TORCH_API at::Tensor & softshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); +TORCH_API at::Tensor & softshrink_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d05ccfce6f26d8e5782067c8ace4a6aad06c7c15 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_softshrink : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & lambd); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5232709bed73287c3d403e3ce24d0350f3cdaa74 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_softshrink_out : public at::meta::structured_softshrink { +void impl(const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sort.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sort.h new file mode 100644 index 0000000000000000000000000000000000000000..92e3107f995a5c037c94f2a874b30af85ac909ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sort.h @@ -0,0 +1,87 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim=-1, bool descending=false) { + return at::_ops::sort_values::call(self, dim, descending, values, indices); +} +// aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_outf(const at::Tensor & self, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices) { + return at::_ops::sort_values::call(self, dim, descending, values, indices); +} + +// aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, ::std::optional stable, int64_t dim=-1, bool descending=false) { + return at::_ops::sort_values_stable::call(self, stable, dim, descending, values, indices); +} +// aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_outf(const at::Tensor & self, ::std::optional stable, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices) { + return at::_ops::sort_values_stable::call(self, stable, dim, descending, values, indices); +} + +// aten::sort(Tensor self, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) +inline ::std::tuple sort(const at::Tensor & self, int64_t dim=-1, bool descending=false) { + return at::_ops::sort::call(self, dim, descending); +} + +// aten::sort.stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) +inline ::std::tuple sort(const at::Tensor & self, ::std::optional stable, int64_t dim=-1, bool descending=false) { + return at::_ops::sort_stable::call(self, stable, dim, descending); +} + +// aten::sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool descending=false) { + return at::_ops::sort_dimname_values::call(self, dim, descending, values, indices); +} +// aten::sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_outf(const at::Tensor & self, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices) { + return at::_ops::sort_dimname_values::call(self, dim, descending, values, indices); +} + +// aten::sort.dimname_values_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, ::std::optional stable, at::Dimname dim, bool descending=false) { + return at::_ops::sort_dimname_values_stable::call(self, stable, dim, descending, values, indices); +} +// aten::sort.dimname_values_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple sort_outf(const at::Tensor & self, ::std::optional stable, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices) { + return at::_ops::sort_dimname_values_stable::call(self, stable, dim, descending, values, indices); +} + +// aten::sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) +inline ::std::tuple sort(const at::Tensor & self, at::Dimname dim, bool descending=false) { + return at::_ops::sort_dimname::call(self, dim, descending); +} + +// aten::sort.dimname_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) +inline ::std::tuple sort(const at::Tensor & self, ::std::optional stable, at::Dimname dim, bool descending=false) { + return at::_ops::sort_dimname_stable::call(self, stable, dim, descending); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sort_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sort_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..a4b8c77d69943fe5891a93f6313fa6f8349cb7ef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sort_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_sort_stable : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, ::std::optional stable, int64_t dim, bool descending); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csr_tensor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csr_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..227ce92d02cee7d825c6e174834f0adcc56c93ec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csr_tensor.h @@ -0,0 +1,49 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sparse_csr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_csr_tensor_crow_col_value_size::call(crow_indices, col_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_csr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_csr_tensor_crow_col_value_size::call(crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); +} + +// aten::sparse_csr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::TensorOptions options) { + return at::_ops::sparse_csr_tensor_crow_col_value::call(crow_indices, col_indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_csr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_csr_tensor_crow_col_value::call(crow_indices, col_indices, values, dtype, layout, device, pin_memory); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2aae61de1bd0a0ef6ca7688d1b9dc241509ac471 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor sparse_resize_and_clear(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +TORCH_API const at::Tensor & sparse_resize_and_clear_out(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out); +TORCH_API const at::Tensor & sparse_resize_and_clear_(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_airy_ai_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_airy_ai_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7b3d1dbf260dd113adb6a4de80452cac2065fb61 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_airy_ai_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_airy_ai_out : public at::meta::structured_special_airy_ai { +void impl(const at::Tensor & x, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j0_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j0_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3ed239932fbb38a218179b4826a2de962034bd18 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j0_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_bessel_j0_out : public at::meta::structured_special_bessel_j0 { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j1_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j1_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf93ce181b06faa1ce61b94436ef3c69b3aedd27 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j1_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_bessel_j1(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0.h new file mode 100644 index 0000000000000000000000000000000000000000..0909eb086515d185e7c012ea944cf5749e8b5bdb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_bessel_y0(Tensor self) -> Tensor +inline at::Tensor special_bessel_y0(const at::Tensor & self) { + return at::_ops::special_bessel_y0::call(self); +} + +// aten::special_bessel_y0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_bessel_y0_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_bessel_y0_out::call(self, out); +} +// aten::special_bessel_y0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_bessel_y0_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_bessel_y0_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6f671ece79d6cd9358d3617f2f1e225159bf34ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_bessel_y0(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y0_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y0_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..014ef28f26a3f895327ba4b671e68cfdf80b06e0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_chebyshev_polynomial_u : public TensorIteratorBase { + + + void meta(const at::Tensor & x, const at::Tensor & n); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_native.h new file mode 100644 index 0000000000000000000000000000000000000000..069c0803ed1b4b8904ca2dcbaf56c1f1fe721122 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_native.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_chebyshev_polynomial_u_out : public at::meta::structured_special_chebyshev_polynomial_u { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_chebyshev_polynomial_u(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_u_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_chebyshev_polynomial_u(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_u_out(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..07990221652a8dd7d04aeeaeccbb0b0d5fc686a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_chebyshev_polynomial_v(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_chebyshev_polynomial_v(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..593c94181a6109a16dc9838673b37fdde2f7e206 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_chebyshev_polynomial_v(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..8b748961dd531648a95a18529df93e33bcf94c58 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_chebyshev_polynomial_v : public TensorIteratorBase { + + + void meta(const at::Tensor & x, const at::Tensor & n); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w.h new file mode 100644 index 0000000000000000000000000000000000000000..e54f021bc0575e917e7f033084d18f73dafc423b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w::call(x, n); +} + +// aten::special_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_w(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w_x_scalar::call(x, n); +} + +// aten::special_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_chebyshev_polynomial_w_n_scalar::call(x, n); +} + +// aten::special_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_w_out::call(x, n, out); +} + +// aten::special_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w_x_scalar_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_w_x_scalar_out::call(x, n, out); +} + +// aten::special_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_chebyshev_polynomial_w_n_scalar_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_w_n_scalar_out::call(x, n, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44259d6d39a43138b66bf35603bcc98e4e1955bd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7f484296d50e6c24abb57cf9495f2ca1c5bb3d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfc.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfc.h new file mode 100644 index 0000000000000000000000000000000000000000..03db20150e8ee9644c70aba0f5ded45d8a3ebc72 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfc.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_erfc(Tensor self) -> Tensor +inline at::Tensor special_erfc(const at::Tensor & self) { + return at::_ops::special_erfc::call(self); +} + +// aten::special_erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_erfc_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_erfc_out::call(self, out); +} +// aten::special_erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_erfc_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_erfc_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfc_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfc_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9e41e54e4990dc2fec69d9c62d880d0a83b96e11 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfc_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_erfc(const at::Tensor & self); +TORCH_API at::Tensor & special_erfc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_erfc_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfcx_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfcx_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..1c9a4b290016b51a0d297ef97a72d25f60da5118 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfcx_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_erfcx : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfinv_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfinv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9be6c111635463905741d71252760c993457ab9a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfinv_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_erfinv { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_erfinv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_erfinv(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_erfinv_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_erfinv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_exp2_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_exp2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b0c30d005a29826d1f212f7cad9969d750d83ad4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_exp2_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_exp2 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_exp2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_exp2(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_exp2_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_exp2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_expit.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_expit.h new file mode 100644 index 0000000000000000000000000000000000000000..f437f1e59fe3944c4e570b31c14ffa1bfad69e85 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_expit.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_expit(Tensor self) -> Tensor +inline at::Tensor special_expit(const at::Tensor & self) { + return at::_ops::special_expit::call(self); +} + +// aten::special_expit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_expit_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_expit_out::call(self, out); +} +// aten::special_expit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_expit_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_expit_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_expm1_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_expm1_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..deffa3d5defb0038f6b65710c6d43611cf9b1267 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_expm1_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_expm1 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_expm1"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_expm1(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_expm1_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_expm1"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammainc.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammainc.h new file mode 100644 index 0000000000000000000000000000000000000000..aff0f00be236597f284afb1c41b4f4be295c52c0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammainc.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_gammainc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_gammainc_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_gammainc_out::call(self, other, out); +} +// aten::special_gammainc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_gammainc_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_gammainc_out::call(self, other, out); +} + +// aten::special_gammainc(Tensor self, Tensor other) -> Tensor +inline at::Tensor special_gammainc(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_gammainc::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc.h new file mode 100644 index 0000000000000000000000000000000000000000..982c5a82d9c898d237701e100fed56d2086c03ff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_gammaincc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_gammaincc_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_gammaincc_out::call(self, other, out); +} +// aten::special_gammaincc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_gammaincc_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_gammaincc_out::call(self, other, out); +} + +// aten::special_gammaincc(Tensor self, Tensor other) -> Tensor +inline at::Tensor special_gammaincc(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_gammaincc::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaln_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaln_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ea81f0fccf271f600d0f1312cfffcb4ca05d1e63 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaln_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_gammaln(const at::Tensor & self); +TORCH_API at::Tensor & special_gammaln_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_gammaln_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97f1172b617674d098da44c7ad197b5b3a177e8b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_hermite_polynomial_h(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_h_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_h_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c5a17298e530b23671d36c6f470d037385928f95 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_hermite_polynomial_he(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e.h new file mode 100644 index 0000000000000000000000000000000000000000..b00da181da7f728aa32f60d3e536e20d4c750a2a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_i0e(Tensor self) -> Tensor +inline at::Tensor special_i0e(const at::Tensor & self) { + return at::_ops::special_i0e::call(self); +} + +// aten::special_i0e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_i0e_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_i0e_out::call(self, out); +} +// aten::special_i0e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_i0e_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_i0e_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..968b1884a7d5d3093ac3f28c699ad08e2ccb16f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor special_i0e(const at::Tensor & self); +TORCH_API at::Tensor & special_i0e_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_i0e_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e2346be8ec2dd2e682db2742eeec97aa3fd14a7f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_i1 : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ac04bcbeafc124d94c20fdf2cd1cd8682a4fe47c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor special_i1e(const at::Tensor & self); +TORCH_API at::Tensor & special_i1e_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_i1e_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0f05c765a28b7089369ac5312cc6795269e2d15d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_laguerre_polynomial_l { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_laguerre_polynomial_l"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_laguerre_polynomial_l(Tensor x, Tensor n) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n); +}; + +struct TORCH_API special_laguerre_polynomial_l_x_scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_laguerre_polynomial_l"; + static constexpr const char* overload_name = "x_scalar"; + static constexpr const char* schema_str = "special_laguerre_polynomial_l.x_scalar(Scalar x, Tensor n) -> Tensor"; + static at::Tensor call(const at::Scalar & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n); +}; + +struct TORCH_API special_laguerre_polynomial_l_n_scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_laguerre_polynomial_l"; + static constexpr const char* overload_name = "n_scalar"; + static constexpr const char* schema_str = "special_laguerre_polynomial_l.n_scalar(Tensor x, Scalar n) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Scalar & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n); +}; + +struct TORCH_API special_laguerre_polynomial_l_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_laguerre_polynomial_l"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_laguerre_polynomial_l_x_scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_laguerre_polynomial_l"; + static constexpr const char* overload_name = "x_scalar_out"; + static constexpr const char* schema_str = "special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_laguerre_polynomial_l_n_scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_laguerre_polynomial_l"; + static constexpr const char* overload_name = "n_scalar_out"; + static constexpr const char* schema_str = "special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5af164b17abfe949032c06208454c96a66fa8fb8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_legendre_polynomial_p(const at::Tensor & x, const at::Tensor & n); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p.h new file mode 100644 index 0000000000000000000000000000000000000000..37307c3d5405b4a6db1a5e881b3aaf6de3325869 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_log1p(Tensor self) -> Tensor +inline at::Tensor special_log1p(const at::Tensor & self) { + return at::_ops::special_log1p::call(self); +} + +// aten::special_log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_log1p_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_log1p_out::call(self, out); +} +// aten::special_log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_log1p_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_log1p_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f9ff6dc921fd67acc97768df2764f5c0cd843b7f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_log_ndtr : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_softmax_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_softmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0943a56bea31f0dfc2f3425e8525fce957070ae3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_softmax_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor special_log_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4b6e4a318d330909066d5ba6accf7627e7cec1b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_modified_bessel_i0(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c06f714fc273c24d1f0b510a36248879e1ab9f1b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_modified_bessel_i1(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..16e20c6407e45bdc2d9e1f273b7273e30ff180d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_modified_bessel_i1 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_modified_bessel_i1"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_modified_bessel_i1(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_modified_bessel_i1_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_modified_bessel_i1"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_modified_bessel_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..549bb80e4eeed15e77930dfd919133f71d0a4fd2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor special_ndtr(const at::Tensor & self); +TORCH_API at::Tensor & special_ndtr_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e6e71c76825e33e1c67c023f38e5a3494345ad1b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_ndtri : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_polygamma.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_polygamma.h new file mode 100644 index 0000000000000000000000000000000000000000..a3fe18894736d9c27fdbff10e855da6fed286ce7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_polygamma.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_polygamma(int n, Tensor self) -> Tensor +inline at::Tensor special_polygamma(int64_t n, const at::Tensor & self) { + return at::_ops::special_polygamma::call(n, self); +} + +// aten::special_polygamma.out(int n, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_polygamma_out(at::Tensor & out, int64_t n, const at::Tensor & self) { + return at::_ops::special_polygamma_out::call(n, self, out); +} +// aten::special_polygamma.out(int n, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_polygamma_outf(int64_t n, const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_polygamma_out::call(n, self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_psi_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_psi_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..05fa3669ca001feb84c0ef3341f7a866bb29e114 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_psi_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_psi { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_psi"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_psi(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_psi_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_psi"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_psi.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0.h new file mode 100644 index 0000000000000000000000000000000000000000..d5a29910019b3206ac2b8cc8462e308345b95ff5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_scaled_modified_bessel_k0(Tensor x) -> Tensor +inline at::Tensor special_scaled_modified_bessel_k0(const at::Tensor & x) { + return at::_ops::special_scaled_modified_bessel_k0::call(x); +} + +// aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_scaled_modified_bessel_k0_out(at::Tensor & out, const at::Tensor & x) { + return at::_ops::special_scaled_modified_bessel_k0_out::call(x, out); +} +// aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_scaled_modified_bessel_k0_outf(const at::Tensor & x, at::Tensor & out) { + return at::_ops::special_scaled_modified_bessel_k0_out::call(x, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..09eaedaa31f0811324e516008f3caad064d9a3ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4620973ec20b432fec66440c07b5f06f5ee98f6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_u(const at::Tensor & x, const at::Tensor & n); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3074b5f1bdaacbfa7b75cac5c4c1aa812af6945e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_shifted_chebyshev_polynomial_u { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_u"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_u_x_scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_u"; + static constexpr const char* overload_name = "x_scalar"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor"; + static at::Tensor call(const at::Scalar & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_u_n_scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_u"; + static constexpr const char* overload_name = "n_scalar"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Scalar & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_u_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_u"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_u_x_scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_u"; + static constexpr const char* overload_name = "x_scalar_out"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_u_n_scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_u"; + static constexpr const char* overload_name = "n_scalar_out"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v.h new file mode 100644 index 0000000000000000000000000000000000000000..68f82a4a0416ad38d166a368378fe7a68e3415ca --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_shifted_chebyshev_polynomial_v(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_v(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_v::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_v.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_v(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_v_x_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_v.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_v(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_v_n_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_v_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_v_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_v_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_v_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_v_x_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_v_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_v_x_scalar_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_v_n_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_v_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_v_n_scalar_out::call(x, n, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e5805d146569c7bb8bf5c3f5f6da910aed4be953 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_v(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_v_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..27051e15d114f9243f356acc3c28cb21d3e7e267 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_w(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_w_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_w_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_w(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f09f4feafa25fb3631a05327f4308b18dcfe663 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_w(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0.h new file mode 100644 index 0000000000000000000000000000000000000000..1946f3b5557da6b876d1be4aeab40e76445caa3e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_spherical_bessel_j0(Tensor x) -> Tensor +inline at::Tensor special_spherical_bessel_j0(const at::Tensor & x) { + return at::_ops::special_spherical_bessel_j0::call(x); +} + +// aten::special_spherical_bessel_j0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_spherical_bessel_j0_out(at::Tensor & out, const at::Tensor & x) { + return at::_ops::special_spherical_bessel_j0_out::call(x, out); +} +// aten::special_spherical_bessel_j0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_spherical_bessel_j0_outf(const at::Tensor & x, at::Tensor & out) { + return at::_ops::special_spherical_bessel_j0_out::call(x, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..67364825a2c7da1b5c34da769a48957bfb83fc6d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_spherical_bessel_j0(const at::Tensor & x); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlog1py_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlog1py_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..73fec9a3ef2dd36d1b169a5ffa46107832b35fba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlog1py_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_xlog1py(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & special_xlog1py_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & special_xlog1py_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor special_xlog1py(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & special_xlog1py_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & special_xlog1py_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta.h new file mode 100644 index 0000000000000000000000000000000000000000..7c70b56bcb7f9f010e166055b7194cfae29350dd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_zeta(Tensor self, Tensor other) -> Tensor +inline at::Tensor special_zeta(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_zeta::call(self, other); +} + +// aten::special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor +inline at::Tensor special_zeta(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_zeta_self_scalar::call(self, other); +} + +// aten::special_zeta.other_scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor special_zeta(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_zeta_other_scalar::call(self, other); +} + +// aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_zeta_out::call(self, other, out); +} +// aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_zeta_out::call(self, other, out); +} + +// aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_zeta_self_scalar_out::call(self, other, out); +} +// aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_zeta_self_scalar_out::call(self, other, out); +} + +// aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_zeta_other_scalar_out::call(self, other, out); +} +// aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::special_zeta_other_scalar_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..637255292131f1c728e495a3bbbee6250562c1bd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_zeta : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..55c053c44dd3248d6e6988cc10f44d602c1bfa0e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API split_copy_Tensor { + using schema = ::std::vector (const at::Tensor &, c10::SymInt, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::split_copy"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "split_copy.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[]"; + static ::std::vector call(const at::Tensor & self, c10::SymInt split_size, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim); +}; + +struct TORCH_API split_copy_Tensor_out { + using schema = void (const at::Tensor &, c10::SymInt, int64_t, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::split_copy"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "split_copy.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()"; + static void call(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e9468d1348f1c419e824922e911cc08605abe9a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void split_with_sizes_copy_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +TORCH_API void split_with_sizes_copy_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out); +TORCH_API void split_with_sizes_copy_symint_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0); +TORCH_API void split_with_sizes_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6dfa23d2b8b219530d2c98b141d9a306b9a09315 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void split_with_sizes_copy_out(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out); +TORCH_API void split_with_sizes_copy_out_cuda(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out); +TORCH_API ::std::vector split_with_sizes_copy_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3dac250fd6dae65187504ef9ccf16eedf277201 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor squeeze(const at::Tensor & self); +TORCH_API at::Tensor & squeeze_(at::Tensor & self); +TORCH_API at::Tensor squeeze(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & squeeze_(at::Tensor & self, int64_t dim); +TORCH_API at::Tensor squeeze(const at::Tensor & self, at::IntArrayRef dim); +TORCH_API at::Tensor & squeeze_(at::Tensor & self, at::IntArrayRef dim); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_native.h new file mode 100644 index 0000000000000000000000000000000000000000..65c5b4205074ea6c5b75896d7df8e840b1b7ae3c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_native.h @@ -0,0 +1,39 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor squeeze(const at::Tensor & self); +TORCH_API at::Tensor squeeze_nested(const at::Tensor & self); +TORCH_API at::Tensor squeeze_quantized(const at::Tensor & self); +TORCH_API at::Tensor & squeeze_(at::Tensor & self); +TORCH_API at::Tensor squeeze(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor squeeze_dim_nested(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor squeeze_quantized(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & squeeze_(at::Tensor & self, int64_t dim); +TORCH_API at::Tensor squeeze(const at::Tensor & self, at::Dimname dim); +TORCH_API at::Tensor & squeeze_(at::Tensor & self, at::Dimname dim); +TORCH_API at::Tensor squeeze(const at::Tensor & self, at::IntArrayRef dim); +TORCH_API at::Tensor squeeze_dim_nested(const at::Tensor & self, at::IntArrayRef dim); +TORCH_API at::Tensor squeeze_quantized(const at::Tensor & self, at::IntArrayRef dim); +TORCH_API at::Tensor & squeeze_(at::Tensor & self, at::IntArrayRef dim); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f1ac1fa61468f0b667435b2e48390ac1bb87ee0e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_ops.h @@ -0,0 +1,111 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API squeeze { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "squeeze(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API squeeze_dim { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "squeeze.dim(Tensor(a) self, int dim) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +struct TORCH_API squeeze_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim); +}; + +struct TORCH_API squeeze_dims { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze"; + static constexpr const char* overload_name = "dims"; + static constexpr const char* schema_str = "squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API squeeze_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "squeeze_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API squeeze__dim { + using schema = at::Tensor & (at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "squeeze_.dim(Tensor(a!) self, int dim) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim); +}; + +struct TORCH_API squeeze__dims { + using schema = at::Tensor & (at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_"; + static constexpr const char* overload_name = "dims"; + static constexpr const char* schema_str = "squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, at::IntArrayRef dim); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API squeeze__dimname { + using schema = at::Tensor & (at::Tensor &, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, at::Dimname dim); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Dimname dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sspaddmm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sspaddmm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6b080fad6cb0a224a2adc5a2af433c86850032f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sspaddmm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sspaddmm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sspaddmm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API sspaddmm_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sspaddmm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stack_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stack_native.h new file mode 100644 index 0000000000000000000000000000000000000000..849a73a8694431dbc7a86de2add5f72cba524e67 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stack_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor stack(at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & stack_out(at::TensorList tensors, int64_t dim, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stack_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stack_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1a79a186cedf268419b8e42157dbc0b31e7f0709 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stack_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API stack { + using schema = at::Tensor (at::TensorList, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::stack"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "stack(Tensor[] tensors, int dim=0) -> Tensor"; + static at::Tensor call(at::TensorList tensors, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, int64_t dim); +}; + +struct TORCH_API stack_out { + using schema = at::Tensor & (at::TensorList, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::stack"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "stack.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::TensorList tensors, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be492b8cd0c77a9be554fe721ad9c72555ad58bc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_compositeimplicitautograd_dispatch.h @@ -0,0 +1,37 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor std(const at::Tensor & self, bool unbiased); +TORCH_API at::Tensor std(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & std_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor std(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & std_outf(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor std(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_outf(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_mean_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_mean_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3335993bf1e13254455d804c61eb722e2beed5d3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_mean_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple std_mean(const at::Tensor & self, bool unbiased); +TORCH_API ::std::tuple std_mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false); +TORCH_API ::std::tuple std_mean(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false); +TORCH_API ::std::tuple std_mean(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_mean_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_mean_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b2b6c7aa96fe4f2ce25218c16e0febd504fe490c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std_mean_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API std_mean { + using schema = ::std::tuple (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::std_mean"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "std_mean(Tensor self, bool unbiased=True) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, bool unbiased); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool unbiased); +}; + +struct TORCH_API std_mean_dim { + using schema = ::std::tuple (const at::Tensor &, at::OptionalIntArrayRef, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::std_mean"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "std_mean.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim); +}; + +struct TORCH_API std_mean_correction { + using schema = ::std::tuple (const at::Tensor &, at::OptionalIntArrayRef, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::std_mean"; + static constexpr const char* overload_name = "correction"; + static constexpr const char* schema_str = "std_mean.correction(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim); +}; + +struct TORCH_API std_mean_names_dim { + using schema = ::std::tuple (const at::Tensor &, at::DimnameList, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::std_mean"; + static constexpr const char* overload_name = "names_dim"; + static constexpr const char* schema_str = "std_mean.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim); +}; + +struct TORCH_API std_mean_correction_names { + using schema = ::std::tuple (const at::Tensor &, at::DimnameList, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::std_mean"; + static constexpr const char* overload_name = "correction_names"; + static constexpr const char* schema_str = "std_mean.correction_names(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim); +}; + +struct TORCH_API std_mean_correction_out { + using schema = ::std::tuple (const at::Tensor &, at::OptionalIntArrayRef, const ::std::optional &, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::std_mean"; + static constexpr const char* overload_name = "correction_out"; + static constexpr const char* schema_str = "std_mean.correction_out(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stft_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stft_native.h new file mode 100644 index 0000000000000000000000000000000000000000..191785e29f2a5e58bac9d27b0eaf904670002dce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stft_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor stft(const at::Tensor & self, int64_t n_fft, ::std::optional hop_length=::std::nullopt, ::std::optional win_length=::std::nullopt, const ::std::optional & window={}, bool normalized=false, ::std::optional onesided=::std::nullopt, ::std::optional return_complex=::std::nullopt, ::std::optional align_to_window=::std::nullopt); +TORCH_API at::Tensor stft(const at::Tensor & self, int64_t n_fft, ::std::optional hop_length=::std::nullopt, ::std::optional win_length=::std::nullopt, const ::std::optional & window={}, bool center=true, c10::string_view pad_mode="reflect", bool normalized=false, ::std::optional onesided=::std::nullopt, ::std::optional return_complex=::std::nullopt, ::std::optional align_to_window=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stft_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stft_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4b840fbc65065043de88e5538ca513e2eea0b3b0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stft_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API stft { + using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional, ::std::optional, const ::std::optional &, bool, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::stft"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "stft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool normalized=False, bool? onesided=None, bool? return_complex=None, bool? align_to_window=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t n_fft, ::std::optional hop_length, ::std::optional win_length, const ::std::optional & window, bool normalized, ::std::optional onesided, ::std::optional return_complex, ::std::optional align_to_window); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n_fft, ::std::optional hop_length, ::std::optional win_length, const ::std::optional & window, bool normalized, ::std::optional onesided, ::std::optional return_complex, ::std::optional align_to_window); +}; + +struct TORCH_API stft_center { + using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional, ::std::optional, const ::std::optional &, bool, c10::string_view, bool, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::stft"; + static constexpr const char* overload_name = "center"; + static constexpr const char* schema_str = "stft.center(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, str pad_mode=\"reflect\", bool normalized=False, bool? onesided=None, bool? return_complex=None, bool? align_to_window=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t n_fft, ::std::optional hop_length, ::std::optional win_length, const ::std::optional & window, bool center, c10::string_view pad_mode, bool normalized, ::std::optional onesided, ::std::optional return_complex, ::std::optional align_to_window); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n_fft, ::std::optional hop_length, ::std::optional win_length, const ::std::optional & window, bool center, c10::string_view pad_mode, bool normalized, ::std::optional onesided, ::std::optional return_complex, ::std::optional align_to_window); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sub_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sub_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..67ef87f31a7462923838f85dfb3673ad50e0fbff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sub_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_sub_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/svd_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/svd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6e8a8a1c516d973f7dfd2b10b9fdc747bade7f39 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/svd_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple svd(const at::Tensor & self, bool some=true, bool compute_uv=true); +TORCH_API ::std::tuple svd_out(const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..68aa230ed95a93090e9c649fc3bf832e13b2d0c6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void sym_constrain_range_for_size(const at::Scalar & size, ::std::optional min=::std::nullopt, ::std::optional max=::std::nullopt); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9c85851c80c6cb5e9e92c30cbaf7b19474a45ab3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void sym_constrain_range_for_size(const at::Scalar & size, ::std::optional min=::std::nullopt, ::std::optional max=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5c7ff05212cfbf2fde544fdc7f7d925b90d5ebb1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_constrain_range_for_size { + using schema = void (const at::Scalar &, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sym_constrain_range_for_size"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sym_constrain_range_for_size(Scalar size, *, int? min=None, int? max=None) -> ()"; + static void call(const at::Scalar & size, ::std::optional min, ::std::optional max); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, ::std::optional min, ::std::optional max); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5acdcb9d9fb2ff15ddc70c855f75323588311cf9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_constrain_range { + using schema = void (const at::Scalar &, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sym_constrain_range"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sym_constrain_range(Scalar size, *, int? min=None, int? max=None) -> ()"; + static void call(const at::Scalar & size, ::std::optional min, ::std::optional max); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, ::std::optional min, ::std::optional max); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_is_contiguous.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_is_contiguous.h new file mode 100644 index 0000000000000000000000000000000000000000..d486f30f91ce497deda98ae5d2894d8c45bbc8fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_is_contiguous.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sym_is_contiguous(Tensor self, MemoryFormat memory_format=contiguous_format) -> SymBool +inline c10::SymBool __dispatch_sym_is_contiguous(const at::Tensor & self, at::MemoryFormat memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::sym_is_contiguous::call(self, memory_format); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_is_contiguous_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_is_contiguous_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..de412bd6fc889b68edaeb3ccf7f5a33f966cc008 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_is_contiguous_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API c10::SymBool sym_is_contiguous(const at::Tensor & self, at::MemoryFormat memory_format=c10::MemoryFormat::Contiguous); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_numel_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_numel_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8cfb5500ac17f40d82881d1d235eeca46d61d50d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_numel_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API c10::SymInt sym_numel(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_storage_offset_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_storage_offset_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2a52f481643a42af2b4d809d4f9a458e4b472467 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_storage_offset_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API c10::SymInt sym_storage_offset(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0e565fc796b210ca04716f6c8efe5f7e1fbbe445 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor t(const at::Tensor & self); +TORCH_API at::Tensor & t_(at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b911315bee3a5fb0753c400deb97bd3f4f35dca0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor t_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tan.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tan.h new file mode 100644 index 0000000000000000000000000000000000000000..f3db4a1ebd6a31b185f2e9537e89e35e842d67da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tan.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::tan(Tensor self) -> Tensor +inline at::Tensor tan(const at::Tensor & self) { + return at::_ops::tan::call(self); +} + +// aten::tan_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & tan_(at::Tensor & self) { + return at::_ops::tan_::call(self); +} + +// aten::tan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tan_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::tan_out::call(self, out); +} +// aten::tan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tan_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::tan_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tan_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tan_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2449d7f1a8e8988dc94847ed298d6afefa4449d9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tan_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor tan(const at::Tensor & self); +TORCH_API at::Tensor & tan_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh.h new file mode 100644 index 0000000000000000000000000000000000000000..73102ae8e73276d21732f44a7c8d451a7228a9c7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::tanh(Tensor self) -> Tensor +inline at::Tensor tanh(const at::Tensor & self) { + return at::_ops::tanh::call(self); +} + +// aten::tanh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & tanh_(at::Tensor & self) { + return at::_ops::tanh_::call(self); +} + +// aten::tanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tanh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::tanh_out::call(self, out); +} +// aten::tanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tanh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::tanh_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7c225ae07c03c3942b8856ddc02567924f1c3238 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor tanh_backward(const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & tanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & tanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f5630e6a8687594ccd381d35d334730ed61c0a1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor tanh(const at::Tensor & self); +TORCH_API at::Tensor & tanh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & tanh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & tanh_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensor_split_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensor_split_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8c6a7f158752ff96f401edbcf6d878d8ab94630a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensor_split_compositeimplicitautograd_dispatch.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::vector tensor_split(const at::Tensor & self, int64_t sections, int64_t dim=0); +TORCH_API ::std::vector tensor_split_symint(const at::Tensor & self, c10::SymInt sections, int64_t dim=0); +TORCH_API ::std::vector tensor_split(const at::Tensor & self, at::IntArrayRef indices, int64_t dim=0); +TORCH_API ::std::vector tensor_split_symint(const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim=0); +TORCH_API ::std::vector tensor_split(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim=0); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensordot.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensordot.h new file mode 100644 index 0000000000000000000000000000000000000000..2482398abc04ca982bac29a5c3c49e23dd64ac0f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensordot.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::tensordot(Tensor self, Tensor other, int[] dims_self, int[] dims_other) -> Tensor +inline at::Tensor tensordot(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other) { + return at::_ops::tensordot::call(self, other, dims_self, dims_other); +} + +// aten::tensordot.out(Tensor self, Tensor other, int[] dims_self, int[] dims_other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tensordot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other) { + return at::_ops::tensordot_out::call(self, other, dims_self, dims_other, out); +} +// aten::tensordot.out(Tensor self, Tensor other, int[] dims_self, int[] dims_other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tensordot_outf(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out) { + return at::_ops::tensordot_out::call(self, other, dims_self, dims_other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensordot_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensordot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e6ee0ccfc2e929a208c19f827fb91b17c231e2c6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tensordot_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor tensordot(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other); +TORCH_API at::Tensor & tensordot_out(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..526f7e21b55768396de83aa0bde4a3e550867f16 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API threshold { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::threshold"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "threshold(Tensor self, Scalar threshold, Scalar value) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +}; + +struct TORCH_API threshold_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::threshold_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "threshold_(Tensor(a!) self, Scalar threshold, Scalar value) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +}; + +struct TORCH_API threshold_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::threshold"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "threshold.out(Tensor self, Scalar threshold, Scalar value, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tile_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tile_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3f7811a5cd3fa21e3093080ae57d93b626f232b7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tile_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor tile(const at::Tensor & self, at::IntArrayRef dims); +TORCH_API at::Tensor tile_symint(const at::Tensor & self, c10::SymIntArrayRef dims); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ecf8dee17fba884039aee1ccd0fe921584b12969 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & to_mkldnn_out(const at::Tensor & self, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor dense_to_mkldnn(const at::Tensor & self, ::std::optional dtype=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4fae366ca72e21162bf7caa4d4633256e7473466 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API to_mkldnn { + using schema = at::Tensor (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to_mkldnn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "to_mkldnn(Tensor self, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype); +}; + +struct TORCH_API to_mkldnn_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to_mkldnn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "to_mkldnn.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_padded_tensor_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_padded_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..33f8980370359d47bd6464afc737afc1d22edd1b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_padded_tensor_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API to_padded_tensor { + using schema = at::Tensor (const at::Tensor &, double, at::OptionalSymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to_padded_tensor"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size); +}; + +struct TORCH_API to_padded_tensor_out { + using schema = at::Tensor & (const at::Tensor &, double, at::OptionalSymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to_padded_tensor"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b01320e253ed67bad6de22e0133a5622778971a1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API to_sparse_sparse_dim { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to_sparse"; + static constexpr const char* overload_name = "sparse_dim"; + static constexpr const char* schema_str = "to_sparse.sparse_dim(Tensor self, int sparse_dim) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t sparse_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sparse_dim); +}; + +struct TORCH_API to_sparse { + using schema = at::Tensor (const at::Tensor &, ::std::optional, at::OptionalIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to_sparse"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional layout, at::OptionalIntArrayRef blocksize, ::std::optional dense_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional layout, at::OptionalIntArrayRef blocksize, ::std::optional dense_dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/topk_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/topk_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7cdc7006bc223f85600f1a9515c538b0daeb246c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/topk_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API topk_values { + using schema = ::std::tuple (const at::Tensor &, c10::SymInt, int64_t, bool, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::topk"; + static constexpr const char* overload_name = "values"; + static constexpr const char* schema_str = "topk.values(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); +}; + +struct TORCH_API topk { + using schema = ::std::tuple (const at::Tensor &, c10::SymInt, int64_t, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::topk"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "topk(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..32697969e9884059609f48fc46cb14392c31adcc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..1f4cc4cde87939af717b885fd6340e185f2e4c79 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::transpose.int(Tensor(a) self, int dim0, int dim1) -> Tensor(a) +inline at::Tensor transpose(const at::Tensor & self, int64_t dim0, int64_t dim1) { + return at::_ops::transpose_int::call(self, dim0, dim1); +} + +// aten::transpose.Dimname(Tensor(a) self, Dimname dim0, Dimname dim1) -> Tensor(a) +inline at::Tensor transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1) { + return at::_ops::transpose_Dimname::call(self, dim0, dim1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b5b424a12bdfbd2d3c9f1ad52dca50aa0f25fe4e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor transpose(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor & transpose_(at::Tensor & self, int64_t dim0, int64_t dim1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7b9265ab5011a28cdf985790ce05d03acb5b05e7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_copy_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & transpose_copy_int_out(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out); +TORCH_API at::Tensor transpose_copy_int(const at::Tensor & self, int64_t dim0, int64_t dim1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..59d4fd7fade0a1c920e1f456784aefe1a75ca9da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API transpose_copy_int { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::transpose_copy"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +struct TORCH_API transpose_copy_int_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::transpose_copy"; + static constexpr const char* overload_name = "int_out"; + static constexpr const char* schema_str = "transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a9f458df316e1475a7f375f6c02e232685d3dadf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API transpose_int { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::transpose"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "transpose.int(Tensor(a) self, int dim0, int dim1) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +struct TORCH_API transpose_Dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::transpose"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "transpose.Dimname(Tensor(a) self, Dimname dim0, Dimname dim1) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim0, at::Dimname dim1); +}; + +struct TORCH_API transpose_ { + using schema = at::Tensor & (at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::transpose_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "transpose_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trapz.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trapz.h new file mode 100644 index 0000000000000000000000000000000000000000..19b4b6b6a0a3068748e3edca832cb2e516fd8dd1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trapz.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor +inline at::Tensor trapz(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1) { + return at::_ops::trapz_x::call(y, x, dim); +} + +// aten::trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor +inline at::Tensor trapz(const at::Tensor & y, double dx=1, int64_t dim=-1) { + return at::_ops::trapz_dx::call(y, dx, dim); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1ad0c0a3daf9796f084eb5bd68459be4d00f7fb3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor tril(const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor tril_symint(const at::Tensor & self, c10::SymInt diagonal=0); +TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & tril__symint(at::Tensor & self, c10::SymInt diagonal=0); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d4df5a0db8a867740a109a566d5098a220b8fda --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1ac8ff49676eb4fe166d3cdc28bb791614c2aea5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API tril_indices { + using schema = at::Tensor (int64_t, int64_t, int64_t, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::tril_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(int64_t row, int64_t col, int64_t offset, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API tril_indices_out { + using schema = at::Tensor & (int64_t, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::tril_indices"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t row, int64_t col, int64_t offset, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..522e6070865b9452e6f02037cd9a9b3a73a8d08e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & triu_indices_out(at::Tensor & out, int64_t row, int64_t col, int64_t offset=0); +TORCH_API at::Tensor & triu_indices_outf(int64_t row, int64_t col, int64_t offset, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a66a83d419a7dcb1f855615520bb381368a07ab5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d7bba260799380cec394ff7681c92474382d912b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_meta_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor triu(const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor triu_symint(const at::Tensor & self, c10::SymInt diagonal=0); +TORCH_API at::Tensor & triu_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & triu_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); +TORCH_API at::Tensor & triu_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt diagonal=0); +TORCH_API at::Tensor & triu_symint_outf(const at::Tensor & self, c10::SymInt diagonal, at::Tensor & out); +TORCH_API at::Tensor & triu_(at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & triu__symint(at::Tensor & self, c10::SymInt diagonal=0); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cc585ffa4c5243c44a636d372c3a92480d10dc12 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API triu_ { + using schema = at::Tensor & (at::Tensor &, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::triu_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "triu_(Tensor(a!) self, SymInt diagonal=0) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, c10::SymInt diagonal); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, c10::SymInt diagonal); +}; + +struct TORCH_API triu_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::triu"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "triu.out(Tensor self, SymInt diagonal=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymInt diagonal, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt diagonal, at::Tensor & out); +}; + +struct TORCH_API triu { + using schema = at::Tensor (const at::Tensor &, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::triu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "triu(Tensor self, SymInt diagonal=0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymInt diagonal); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt diagonal); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b75388dc5a0a9a738a1cd6007cd74ff4d46785ec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API type_as { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::type_as"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "type_as(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37369b15dd873525ed00d76c61f9d9d32ee970be --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::vector unbind(const at::Tensor & self, at::Dimname dim); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..68621df6eb61dced321186c1d4b4326c3589959d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_copy.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::unbind_copy.int(Tensor self, int dim=0) -> Tensor[] +inline ::std::vector unbind_copy(const at::Tensor & self, int64_t dim=0) { + return at::_ops::unbind_copy_int::call(self, dim); +} + +// aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () +inline void unbind_copy_out(at::TensorList out, const at::Tensor & self, int64_t dim=0) { + return at::_ops::unbind_copy_int_out::call(self, dim, out); +} +// aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () +inline void unbind_copy_outf(const at::Tensor & self, int64_t dim, at::TensorList out) { + return at::_ops::unbind_copy_int_out::call(self, dim, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..072f72d23fa0193ccc3a85cde96c4aec77419e60 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor unflatten(const at::Tensor & self, int64_t dim, at::IntArrayRef sizes); +TORCH_API at::Tensor unflatten_symint(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes); +TORCH_API at::Tensor unflatten(const at::Tensor & self, at::Dimname dim, at::IntArrayRef sizes, at::DimnameList names); +TORCH_API at::Tensor unflatten_symint(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a841e1b6031faaa573968d6b2075c97cf418f503 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector unflatten_dense_tensors(const at::Tensor & flat, at::TensorList tensors); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_native.h new file mode 100644 index 0000000000000000000000000000000000000000..784390e30335b224150250d6326c90171121eb43 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unflatten_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor unflatten_symint(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes); +TORCH_API at::Tensor unflatten_dimname_symint(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..1fc657d3cb32f3b0076ce218647537adc76c0f18 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor +inline at::Tensor unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) { + return at::_ops::unfold_copy::call(self, dimension, size, step); +} + +// aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & unfold_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) { + return at::_ops::unfold_copy_out::call(self, dimension, size, step, out); +} +// aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & unfold_copy_outf(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out) { + return at::_ops::unfold_copy_out::call(self, dimension, size, step, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..82b3f0a817e7b29c9a675077ff9538c3d4711b46 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & unfold_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); +TORCH_API at::Tensor & unfold_copy_outf(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cd90a697cf0a8f3c2db224a526bbfa6bae6dab02 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1a3d3b6008169b231cf3a0f9f842db6c542be3b5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..785055511a03466b9d59da907b1fffbf6f1d4a2c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API unsafe_split_Tensor { + using schema = ::std::vector (const at::Tensor &, c10::SymInt, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::unsafe_split"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[]"; + static ::std::vector call(const at::Tensor & self, c10::SymInt split_size, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim); +}; + +struct TORCH_API unsafe_split_Tensor_out { + using schema = void (const at::Tensor &, c10::SymInt, int64_t, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::unsafe_split"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()"; + static void call(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes.h new file mode 100644 index 0000000000000000000000000000000000000000..aba5e57625ec88ec2145a1677d40d509fed4a65c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] +inline ::std::vector unsafe_split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes::call(self, c10::fromIntArrayRefSlow(split_sizes), dim); +} +namespace symint { + template >> + ::std::vector unsafe_split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes::call(self, c10::fromIntArrayRefSlow(split_sizes), dim); + } +} + +// aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] +inline ::std::vector unsafe_split_with_sizes_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes::call(self, split_sizes, dim); +} +namespace symint { + template >> + ::std::vector unsafe_split_with_sizes(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes::call(self, split_sizes, dim); + } +} + +// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () +inline void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out); +} +namespace symint { + template >> + void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out); + } +} + +// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () +inline void unsafe_split_with_sizes_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out) { + return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out); +} +namespace symint { + template >> + void unsafe_split_with_sizes_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out) { + return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out); + } +} + +// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () +inline void unsafe_split_with_sizes_symint_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out); +} +namespace symint { + template >> + void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) { + return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out); + } +} + +// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () +inline void unsafe_split_with_sizes_symint_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) { + return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out); +} +namespace symint { + template >> + void unsafe_split_with_sizes_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) { + return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..1e95394f942464a7c13b5ac3df10b89e6fd9c14b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::unsqueeze_copy(Tensor self, int dim) -> Tensor +inline at::Tensor unsqueeze_copy(const at::Tensor & self, int64_t dim) { + return at::_ops::unsqueeze_copy::call(self, dim); +} + +// aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & unsqueeze_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim) { + return at::_ops::unsqueeze_copy_out::call(self, dim, out); +} +// aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & unsqueeze_copy_outf(const at::Tensor & self, int64_t dim, at::Tensor & out) { + return at::_ops::unsqueeze_copy_out::call(self, dim, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..20cf4e4b04df3052f1e4f1b608f5921ec4a6ebd3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor unsqueeze_copy(const at::Tensor & self, int64_t dim); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2cc5944f4909fb480a05e69f56f1a1d6ecd7239a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13e4c4df03bea4d18249e33b89df39d6546aa749 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..3c60a3842083af9404286d3f0e6cb3d2f68e9525 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_upsample_bicubic2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..83a31a20a91d7d300a3754b1b37cccb1985d1036 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_upsample_bilinear2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..889234bdd5b2d8a886c5fa3f0a4b864131831648 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c270c71d8bf4b094667812f687ac35881ac21efc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d2905d80cd04a9e19a7f5f0ff07dba8e4bd87c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3d4d8f5f1644c9678985e15aba4b9343b2ad1438 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API upsample_bilinear2d_vec { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional>); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_bilinear2d"; + static constexpr const char* overload_name = "vec"; + static constexpr const char* schema_str = "upsample_bilinear2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor"; + static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +}; + +struct TORCH_API upsample_bilinear2d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_bilinear2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "upsample_bilinear2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +}; + +struct TORCH_API upsample_bilinear2d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_bilinear2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_bilinear2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); +}; + +struct TORCH_API upsample_bilinear2d_vec_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional>, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_bilinear2d"; + static constexpr const char* overload_name = "vec_out"; + static constexpr const char* schema_str = "upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d1451c1146120e8c24a4c59458d99564b6d6b08 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_linear1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b44b64280b4695959ef444183859830cc10fdc7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales, at::Tensor & out); +TORCH_API at::Tensor & upsample_linear1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..12f13a8bc47d7a5e2416f2cc09520d41a86fe97c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..588272d84a381f3f13cab4d6346fe9e3d1e6ff68 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bcbeea703c05029c0eee1eacf1f43f875bef92a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_native.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +TORCH_API at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +struct TORCH_API structured_upsample_nearest1d_out_cpu : public at::meta::structured_upsample_nearest1d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales, const at::Tensor & out); +}; +struct TORCH_API structured_upsample_nearest1d_out_cuda : public at::meta::structured_upsample_nearest1d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..32acc46c70e5429bde3bffb8eacc1d442d841790 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fabc870de3c432fccb8ad0c943515fb00771c265 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1079ca478abeab92be748e6e7f96271b9f6caf41 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a3751c24239df36554b5562e559817eaac564e56 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..bdf738987c9bd8f242c0cafab1574fab0dedf493 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); + } +} + +// aten::upsample_nearest3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f509fe9a7b4b775ac8ae85a5694b33416b333a97 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_upsample_nearest3d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..510830315658c3fef143d4ffccbcf3991586cd6b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API upsample_nearest3d_vec { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, ::std::optional>); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_nearest3d"; + static constexpr const char* overload_name = "vec"; + static constexpr const char* schema_str = "upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor"; + static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); +}; + +struct TORCH_API upsample_nearest3d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_nearest3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "upsample_nearest3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +}; + +struct TORCH_API upsample_nearest3d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_nearest3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_nearest3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d.h new file mode 100644 index 0000000000000000000000000000000000000000..bdab3e9cd380872fe9f2b4e9cb527e9733e5ad17 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d.h @@ -0,0 +1,119 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_trilinear3d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_trilinear3d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_trilinear3d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_trilinear3d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); + } +} + +// aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_trilinear3d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_trilinear3d_vec::call(input, output_size, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_trilinear3d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_trilinear3d_vec::call(input, output_size, align_corners, scale_factors); + } +} + +// aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_d, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_d, scales_h, scales_w, out); + } +} + +// aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_trilinear3d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_d, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_trilinear3d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_d, scales_h, scales_w, out); + } +} + +// aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_trilinear3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d_out::call(self, output_size, align_corners, scales_d, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d_out::call(self, output_size, align_corners, scales_d, scales_h, scales_w, out); + } +} + +// aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_trilinear3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_trilinear3d_out::call(self, output_size, align_corners, scales_d, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_trilinear3d_out::call(self, output_size, align_corners, scales_d, scales_h, scales_w, out); + } +} + +// aten::upsample_trilinear3d(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_trilinear3d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_d, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_trilinear3d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_d, scales_h, scales_w); + } +} + +// aten::upsample_trilinear3d(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_trilinear3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d::call(self, output_size, align_corners, scales_d, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_trilinear3d(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_trilinear3d::call(self, output_size, align_corners, scales_d, scales_h, scales_w); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c19177a5d9071258009fc658053bc9e5e5ec789 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_trilinear3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_trilinear3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_trilinear3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/values.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/values.h new file mode 100644 index 0000000000000000000000000000000000000000..d4bbc26c99ba9634d462aba1db550376481a12d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/values.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/values_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/values_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e9a2d43eb885988a455de3dfb0030bfd9a25d381 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/values_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor values_default(const at::Tensor & self); +TORCH_API at::Tensor values_nested(const at::Tensor & self); +TORCH_API at::Tensor values_sparse(const at::Tensor & self); +TORCH_API at::Tensor values_sparse_csr(const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex.h new file mode 100644 index 0000000000000000000000000000000000000000..103df5055d18aa2babc2eb9664b1b57e349baa86 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::view_as_complex(Tensor(a) self) -> Tensor(a) +inline at::Tensor view_as_complex(const at::Tensor & self) { + return at::_ops::view_as_complex::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..87d25c1dcd4f185e35f46f714d1ec32f805c00d7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_copy.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::view_as_complex_copy(Tensor self) -> Tensor +inline at::Tensor view_as_complex_copy(const at::Tensor & self) { + return at::_ops::view_as_complex_copy::call(self); +} + +// aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_as_complex_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::view_as_complex_copy_out::call(self, out); +} +// aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_as_complex_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::view_as_complex_copy_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7460df92c779dd9c7d1869a684ee495593cf80ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor view_as_complex(const at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e339556c570e1dc2e5dffa89b011ad77f0ba49e1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_meta_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor view_as_complex(const at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real.h new file mode 100644 index 0000000000000000000000000000000000000000..fe61e8c7f6492e8ec98308959abdacd247064026 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::view_as_real(Tensor(a) self) -> Tensor(a) +inline at::Tensor view_as_real(const at::Tensor & self) { + return at::_ops::view_as_real::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9fca166e21a6e632282acf1f8ce5bac6de4ece3c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_meta_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor view_as_real(const at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c23ccc99e3df0e952961f829f1fb4d19d1af8bf9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor view_copy(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor view_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size); +TORCH_API at::Tensor view_copy(const at::Tensor & self, at::ScalarType dtype); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f83ee680abe75ff7fc72c64ed81dc12f77f9342a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & view_copy_out_symint(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor view_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size); +TORCH_API at::Tensor & view_copy_dtype_out(const at::Tensor & self, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor view_copy_dtype(const at::Tensor & self, at::ScalarType dtype); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/vstack.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/vstack.h new file mode 100644 index 0000000000000000000000000000000000000000..181e5b9a66a52491cbe6f755a38ee2fedd71ac36 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/vstack.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::vstack(Tensor[] tensors) -> Tensor +inline at::Tensor vstack(at::TensorList tensors) { + return at::_ops::vstack::call(tensors); +} + +// aten::vstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & vstack_out(at::Tensor & out, at::TensorList tensors) { + return at::_ops::vstack_out::call(tensors, out); +} +// aten::vstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & vstack_outf(at::TensorList tensors, at::Tensor & out) { + return at::_ops::vstack_out::call(tensors, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where.h new file mode 100644 index 0000000000000000000000000000000000000000..98b602d9fd4fc1a05b13f230abe9815bafe01bf5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where.h @@ -0,0 +1,65 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::where.self(Tensor condition, Tensor self, Tensor other) -> Tensor +inline at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::where_self::call(condition, self, other); +} + +// aten::where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & where_out(at::Tensor & out, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::where_self_out::call(condition, self, other, out); +} +// aten::where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & where_outf(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::where_self_out::call(condition, self, other, out); +} + +// aten::where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> Tensor +inline at::Tensor where(const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::where_ScalarSelf::call(condition, self, other); +} + +// aten::where.ScalarOther(Tensor condition, Tensor self, Scalar other) -> Tensor +inline at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::where_ScalarOther::call(condition, self, other); +} + +// aten::where.Scalar(Tensor condition, Scalar self, Scalar other) -> Tensor +inline at::Tensor where(const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other) { + return at::_ops::where_Scalar::call(condition, self, other); +} + +// aten::where(Tensor condition) -> Tensor[] +inline ::std::vector where(const at::Tensor & condition) { + return at::_ops::where::call(condition); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2cb48cb4c7c866d667250a19f8fbfe0f7235101c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & where_out(at::Tensor & out, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & where_outf(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9ad14f353a1bb242425f721608bf8643f5345db3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/where_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & where_self_out(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor NestedTensor_where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & NestedTensor_where_out(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other); +TORCH_API ::std::vector where(const at::Tensor & condition); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zero.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zero.h new file mode 100644 index 0000000000000000000000000000000000000000..9cb89bf96a592c91aedfd4fad33f25b2ddbef542 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zero.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::zero_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & zero_(at::Tensor & self) { + return at::_ops::zero_::call(self); +} + +// aten::zero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zero_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::zero_out::call(self, out); +} +// aten::zero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zero_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::zero_out::call(self, out); +} + +// aten::zero(Tensor self) -> Tensor +inline at::Tensor zero(const at::Tensor & self) { + return at::_ops::zero::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_like_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_like_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6eea28cb4c7b43d2260a71e204f5be7e719c49d9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_like_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor zeros_like(const at::Tensor & self, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor zeros_like(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +TORCH_API at::Tensor & zeros_like_out(at::Tensor & out, const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & zeros_like_outf(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_like_compositeimplicitautogradnestedtensor_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_like_compositeimplicitautogradnestedtensor_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a19709ee6e3fd4421f8914892c48832efc6c665a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_like_compositeimplicitautogradnestedtensor_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautogradnestedtensor { + +TORCH_API at::Tensor zeros_like(const at::Tensor & self, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor zeros_like(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + +} // namespace compositeimplicitautogradnestedtensor +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c432f23fd43ce8dc9556dd4e6213709c3548aec4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/zeros_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor zeros(at::IntArrayRef size, ::std::optional names, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & zeros_names_out(at::IntArrayRef size, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor zeros_symint(c10::SymIntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & zeros_out(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & zeros_sparse_out(at::IntArrayRef size, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)