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a/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/tzdata/zoneinfo/Indian/Reunion b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/tzdata/zoneinfo/Indian/Reunion new file mode 100644 index 0000000000000000000000000000000000000000..58d75bc26eec90272e97696f40483eb56c2b8b45 Binary files /dev/null and b/Prism/LLaDA/LLaDA_Prism/.venv/lib/python3.12/site-packages/tzdata/zoneinfo/Indian/Reunion differ diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7294610b2f63dd11f3babf8f21e6897e0cc4f150 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_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 & _adaptive_avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor & _adaptive_avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor & _adaptive_avg_pool2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size); +TORCH_API at::Tensor & _adaptive_avg_pool2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, 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/_adaptive_avg_pool3d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..11c0244213c3d3c62d99b45302284c7c29204579 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_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::_adaptive_avg_pool3d_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor _adaptive_avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::_adaptive_avg_pool3d_backward::call(grad_output, self); +} + +// aten::_adaptive_avg_pool3d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool3d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::_adaptive_avg_pool3d_backward_out::call(grad_output, self, out); +} +// aten::_adaptive_avg_pool3d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { + return at::_ops::_adaptive_avg_pool3d_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/_add_relu_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9d719a8ddc36a60f74d57b4ed3f3e047308d3fe7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_add_relu_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 _add_relu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _add_relu_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _add_relu_outf(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(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 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/_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..32ec31050bcb217753208d1604ea0e859d6071b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_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 _aminmax { + using schema = ::std::tuple (const 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 = ""; + static constexpr const char* schema_str = "_aminmax(Tensor self) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _aminmax_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::_aminmax"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "_aminmax.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor, Tensor)"; + 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 _aminmax_out { + using schema = ::std::tuple (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::_aminmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_aminmax.out(Tensor self, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out0, at::Tensor & out1); +}; + +struct TORCH_API _aminmax_dim_out { + 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::_aminmax"; + static constexpr const char* overload_name = "dim_out"; + static constexpr const char* schema_str = "_aminmax.dim_out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, 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/_amp_foreach_non_finite_check_and_unscale_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ac76806ceb02bc651e9c8f83c00bacd615a60c9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale_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 _amp_foreach_non_finite_check_and_unscale_(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_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/_amp_update_scale_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_update_scale_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b012adfc8f62b6a456ea21e5fb89ebffbf4f6dd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_amp_update_scale_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 ::std::tuple _amp_update_scale(const at::Tensor & self, const at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval); +TORCH_API at::Tensor & _amp_update_scale_out(at::Tensor & out, const at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval); +TORCH_API at::Tensor & _amp_update_scale_outf(const at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval, 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/_assert_async.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_async.h new file mode 100644 index 0000000000000000000000000000000000000000..9a4e1a0ee8f2cddd0b9bec19b04800db05d501ba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_async.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::_assert_async(Tensor self) -> () +inline void _assert_async(const at::Tensor & self) { + return at::_ops::_assert_async::call(self); +} + +// aten::_assert_async.msg(Tensor self, str assert_msg) -> () +inline void _assert_async(const at::Tensor & self, c10::string_view assert_msg) { + return at::_ops::_assert_async_msg::call(self, assert_msg); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_async_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_async_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5ee01c15656b13bd917ec0a1c8e8e0dfdd6cedcc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_async_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 void _assert_async_cpu(const at::Tensor & self); +TORCH_API void _assert_async_cuda(const at::Tensor & self); +TORCH_API void _assert_async_msg_cpu(const at::Tensor & self, c10::string_view assert_msg); +TORCH_API void _assert_async_msg_cuda(const at::Tensor & self, c10::string_view assert_msg); +} // 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/_assert_tensor_metadata_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_tensor_metadata_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..400f265e6c9973c2b8323f5e413a8a8a353f65f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_tensor_metadata_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_tensor_metadata { + using schema = void (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalSymIntArrayRef, ::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::_assert_tensor_metadata"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_assert_tensor_metadata(Tensor a, SymInt[]? size=None, SymInt[]? stride=None, ScalarType? dtype=None, *, Device? device=None, Layout? layout=None) -> ()"; + static void call(const at::Tensor & a, at::OptionalSymIntArrayRef size, at::OptionalSymIntArrayRef stride, ::std::optional dtype, ::std::optional device, ::std::optional layout); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & a, at::OptionalSymIntArrayRef size, at::OptionalSymIntArrayRef stride, ::std::optional dtype, ::std::optional device, ::std::optional layout); +}; + +}} // 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_reduced_precision_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_autocast_to_reduced_precision_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4f6f669e28feb677de7bdbe74d3f7bdd81f787a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_autocast_to_reduced_precision_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 _autocast_to_reduced_precision { + using schema = at::Tensor (const at::Tensor &, bool, bool, at::ScalarType, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_autocast_to_reduced_precision"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_autocast_to_reduced_precision(Tensor(a) self, bool cuda_enabled, bool cpu_enabled, ScalarType cuda_dtype, ScalarType cpu_dtype) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, bool cuda_enabled, bool cpu_enabled, at::ScalarType cuda_dtype, at::ScalarType cpu_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool cuda_enabled, bool cpu_enabled, at::ScalarType cuda_dtype, at::ScalarType cpu_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/_batch_norm_no_update_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_no_update_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..13cfa92a7b6dc0aa7c8b7563cd906097ee089e19 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_no_update_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 _batch_norm_no_update { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_batch_norm_no_update"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_batch_norm_no_update(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _batch_norm_no_update_out { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, double, 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::_batch_norm_no_update"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_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!))"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +}} // 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_with_update_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_with_update_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d7d223f6a6cd430af593630702b8656d7a08e0ea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_with_update_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 _batch_norm_with_update_functional(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps); +TORCH_API ::std::tuple _batch_norm_with_update_cpu_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, at::Tensor & reserve); +TORCH_API ::std::tuple _batch_norm_with_update_cpu(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps); +TORCH_API ::std::tuple _batch_norm_with_update_cuda_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, at::Tensor & reserve); +TORCH_API ::std::tuple _batch_norm_with_update_cuda(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps); +TORCH_API ::std::tuple _batch_norm_with_update_mkldnn(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, 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/_cast_Char_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..097a0f306e6632e64f17e00207b4182b26ed5037 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char_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 _cast_Char { + 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::_cast_Char"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cast_Char(Tensor self, bool non_blocking=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking); +}; + +}} // 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/_cast_Half_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Half_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cfe4fc5149de01f790c9d87c04c3b57c84048d12 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Half_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 _cast_Half { + 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::_cast_Half"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cast_Half(Tensor self, bool non_blocking=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking); +}; + +}} // 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/_cast_Long_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Long_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0ff6bc587e110e4065ae7ac72f23b6abd3ab039b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Long_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 _cast_Long { + 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::_cast_Long"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cast_Long(Tensor self, bool non_blocking=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking); +}; + +}} // 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/_cast_Short_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Short_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..18b6f4f7ef04bdaa58ad2f3d9ee799c1fe39328b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Short_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 _cast_Short { + 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::_cast_Short"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cast_Short(Tensor self, bool non_blocking=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking); +}; + +}} // 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/_cdist_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9382431cd01197b0215703df5c3ae874d3283b37 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_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 _cdist_backward(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist); + +} // 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/_cdist_forward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d4a2ea590e58dcfccef51adf057f5be6674d357 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_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 _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); + +} // 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/_chunk_cat_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0c9fb1280e062604f43f16a8b57f1bec5f205905 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat_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 _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 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/_coalesced_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c79655d6bfbcdfdd0f8ce068fbfba08b06240dc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_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 _coalesced(const at::Tensor & self, bool coalesced); +TORCH_API at::Tensor & _coalesced_out(const at::Tensor & self, bool coalesced, at::Tensor & out); +TORCH_API at::Tensor & _coalesced_sparse_(at::Tensor & self, bool coalesced); +} // 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/_compute_linear_combination_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a09ee03b4eb4a1c8a9b057bcf96c9cd03001240 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_compute_linear_combination_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 _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 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/_conj_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..1bc07bae430712912168a5dcb29b3c306ae494e3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_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::_conj_copy(Tensor self) -> Tensor +inline at::Tensor _conj_copy(const at::Tensor & self) { + return at::_ops::_conj_copy::call(self); +} + +// aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _conj_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_conj_copy_out::call(self, out); +} +// aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _conj_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_conj_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/_convert_weight_to_int4pack_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6ad3d7eeb73b286dc2aa6846503b4e95f6e05ecd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_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 _convert_weight_to_int4pack(const at::Tensor & self, int64_t innerKTiles); + +} // 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/_convert_weight_to_int4pack_for_cpu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu.h new file mode 100644 index 0000000000000000000000000000000000000000..aae8e5042b9a8284ac4cfeefb122404e6603c011 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu.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::_convert_weight_to_int4pack_for_cpu(Tensor self, int innerKTiles) -> Tensor +inline at::Tensor _convert_weight_to_int4pack_for_cpu(const at::Tensor & self, int64_t innerKTiles) { + return at::_ops::_convert_weight_to_int4pack_for_cpu::call(self, innerKTiles); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode.h new file mode 100644 index 0000000000000000000000000000000000000000..bc2a2e64230b148cd22eb67afef77fe88808fa2d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_mode.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::_convolution_mode(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, str padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _convolution_mode(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_convolution_mode::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor _convolution_mode(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_convolution_mode::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::_convolution_mode(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, str padding, SymInt[] dilation, SymInt groups) -> Tensor +inline 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) { + return at::_ops::_convolution_mode::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + at::Tensor _convolution_mode(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) { + return at::_ops::_convolution_mode::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/_copy_from_and_resize_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_copy_from_and_resize_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a0cf17ccfdefe6e073d89d3f23c08497860f15e8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_copy_from_and_resize_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 _copy_from_and_resize { + 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::_copy_from_and_resize"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_copy_from_and_resize(Tensor self, Tensor dst) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & dst); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & dst); +}; + +struct TORCH_API _copy_from_and_resize_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::_copy_from_and_resize"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_copy_from_and_resize.out(Tensor self, Tensor dst, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & dst, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & dst, 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/_cslt_sparse_mm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c33c034618f577853cf941e429579970895614a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_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 _cslt_sparse_mm(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias={}, const ::std::optional & alpha={}, ::std::optional out_dtype=::std::nullopt, bool transpose_result=false, int64_t alg_id=0, int64_t split_k=1, int64_t split_k_mode=-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/_cslt_sparse_mm_search_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..410d06989f7c48bb8872815281faaff06f496c3a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_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 int64_t _cslt_sparse_mm_search(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias={}, const ::std::optional & alpha={}, ::std::optional out_dtype=::std::nullopt, bool transpose_result=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/_ctc_loss_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d661df33586ce795b00902dbc115183f6565903a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_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 _ctc_loss_out(at::Tensor & out0, at::Tensor & out1, 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_outf(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_out(at::Tensor & out0, at::Tensor & out1, 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); +TORCH_API ::std::tuple _ctc_loss_outf(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 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_attention_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6b04819a754858d9ec423c09c79abd0ab5933753 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_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 _cudnn_attention_backward(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, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, ::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/_cudnn_attention_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1e39055877b285bf32c755f8c0e47deef209722 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_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 _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::_cudnn_attention_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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/_cudnn_attention_forward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c63ea70606899e95322eee59168e49b9e63e8da4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_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 _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); +TORCH_API ::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); + +} // 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_attention_forward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f36bf874f40467b62e656ec893455a46bfec9c39 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_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 _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); +} // 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_ctc_loss_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ccb9bd5069ad0a5e1b2281050771f139447ad78 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_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 ::std::tuple _cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity); +TORCH_API ::std::tuple _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, bool deterministic, bool zero_infinity); + +} // 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/_cufft_clear_plan_cache_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e7c95905caa3e9c1c2131306d1ac9223dbaff93e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_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 _cufft_clear_plan_cache(at::DeviceIndex device_index); + +} // 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/_cufft_clear_plan_cache_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..355a8692d7982c85776e9642796f23a8a9b9c30d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_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 _cufft_clear_plan_cache { + using schema = void (at::DeviceIndex); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cufft_clear_plan_cache"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cufft_clear_plan_cache(DeviceIndex device_index) -> ()"; + static void call(at::DeviceIndex device_index); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::DeviceIndex device_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/_cufft_get_plan_cache_max_size_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b00f1ed7629e09dbccc03b28f3cb1e2443fe3409 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_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 int64_t _cufft_get_plan_cache_max_size(at::DeviceIndex device_index); +} // 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/_cummax_helper_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummax_helper_native.h new file mode 100644 index 0000000000000000000000000000000000000000..05323e563a17883f6cb2d0f9500b6cf52b9501b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummax_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 cummax_helper_cpu(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +TORCH_API void cummax_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/_cummin_helper.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..d231bc46d39943fe9f7aa697d8f8375dac510018 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper.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::_cummin_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> () +inline void _cummin_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim) { + return at::_ops::_cummin_helper::call(self, values, indices, 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/_cummin_helper_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_helper_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..002ec7e4196375c534238a9124da0bf2fc8de6f3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_cummin_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 _cummin_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/_dirichlet_grad_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3f8ecf117b54ad6e04b3f52857ea2a48e628e953 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_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 & _dirichlet_grad_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); +TORCH_API at::Tensor & _dirichlet_grad_outf(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, 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/_dirichlet_grad_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..89d38a57a70f2e857f794f5113ebfc8b9d4ed51a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_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 _dirichlet_grad(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); + +} // 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/_dirichlet_grad_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ca79352c2326048858db780c10a55853ef81bf3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_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 _dirichlet_grad(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); + +} // 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/_dyn_quant_matmul_4bit_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2a2f8d498fe7544ebf1a4a920c1200d693715199 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_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 _dyn_quant_matmul_4bit { + using schema = 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::_dyn_quant_matmul_4bit"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dyn_quant_matmul_4bit(Tensor inp, Tensor packed_weights, int block_size, int in_features, int out_features) -> Tensor"; + static at::Tensor call(const at::Tensor & inp, const at::Tensor & packed_weights, int64_t block_size, int64_t in_features, int64_t out_features); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & inp, const at::Tensor & packed_weights, int64_t block_size, int64_t in_features, int64_t out_features); +}; + +}} // 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/_dyn_quant_pack_4bit_weight_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b66d8cf450c726c549cd65e1ed8e193338995e47 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_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 _dyn_quant_pack_4bit_weight { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, 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::_dyn_quant_pack_4bit_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dyn_quant_pack_4bit_weight(Tensor weights, Tensor scales_zeros, Tensor? bias, int block_size, int in_features, int out_features) -> Tensor"; + static at::Tensor call(const at::Tensor & weights, const at::Tensor & scales_zeros, const ::std::optional & bias, int64_t block_size, int64_t in_features, int64_t out_features); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weights, const at::Tensor & scales_zeros, const ::std::optional & bias, int64_t block_size, int64_t in_features, int64_t out_features); +}; + +}} // 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/_efficient_attention_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..b49aac51258dd13a74274d0cda3c89a258dfa9ae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_backward.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::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor out, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt max_seqlen_q, SymInt max_seqlen_k, Tensor logsumexp, float dropout_p, Tensor philox_seed, Tensor philox_offset, int custom_mask_type, bool bias_requires_grad, *, float? scale=None, int? num_splits_key=None, int? window_size=None, bool shared_storage_dqdkdv=False) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _efficient_attention_backward(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const at::Tensor & out, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, int64_t max_seqlen_q, int64_t max_seqlen_k, const at::Tensor & logsumexp, double dropout_p, const at::Tensor & philox_seed, const at::Tensor & philox_offset, int64_t custom_mask_type, bool bias_requires_grad, ::std::optional scale=::std::nullopt, ::std::optional num_splits_key=::std::nullopt, ::std::optional window_size=::std::nullopt, bool shared_storage_dqdkdv=false) { + return at::_ops::_efficient_attention_backward::call(grad_out_, query, key, value, bias, out, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, logsumexp, dropout_p, philox_seed, philox_offset, custom_mask_type, bias_requires_grad, scale, num_splits_key, window_size, shared_storage_dqdkdv); +} +namespace symint { + template >> + ::std::tuple _efficient_attention_backward(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const at::Tensor & out, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, int64_t max_seqlen_q, int64_t max_seqlen_k, const at::Tensor & logsumexp, double dropout_p, const at::Tensor & philox_seed, const at::Tensor & philox_offset, int64_t custom_mask_type, bool bias_requires_grad, ::std::optional scale=::std::nullopt, ::std::optional num_splits_key=::std::nullopt, ::std::optional window_size=::std::nullopt, bool shared_storage_dqdkdv=false) { + return at::_ops::_efficient_attention_backward::call(grad_out_, query, key, value, bias, out, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, logsumexp, dropout_p, philox_seed, philox_offset, custom_mask_type, bias_requires_grad, scale, num_splits_key, window_size, shared_storage_dqdkdv); + } +} + +// aten::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor out, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt max_seqlen_q, SymInt max_seqlen_k, Tensor logsumexp, float dropout_p, Tensor philox_seed, Tensor philox_offset, int custom_mask_type, bool bias_requires_grad, *, float? scale=None, int? num_splits_key=None, int? window_size=None, bool shared_storage_dqdkdv=False) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _efficient_attention_backward_symint(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const at::Tensor & out, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, c10::SymInt max_seqlen_q, c10::SymInt max_seqlen_k, const at::Tensor & logsumexp, double dropout_p, const at::Tensor & philox_seed, const at::Tensor & philox_offset, int64_t custom_mask_type, bool bias_requires_grad, ::std::optional scale=::std::nullopt, ::std::optional num_splits_key=::std::nullopt, ::std::optional window_size=::std::nullopt, bool shared_storage_dqdkdv=false) { + return at::_ops::_efficient_attention_backward::call(grad_out_, query, key, value, bias, out, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, logsumexp, dropout_p, philox_seed, philox_offset, custom_mask_type, bias_requires_grad, scale, num_splits_key, window_size, shared_storage_dqdkdv); +} +namespace symint { + template >> + ::std::tuple _efficient_attention_backward(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const at::Tensor & out, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, c10::SymInt max_seqlen_q, c10::SymInt max_seqlen_k, const at::Tensor & logsumexp, double dropout_p, const at::Tensor & philox_seed, const at::Tensor & philox_offset, int64_t custom_mask_type, bool bias_requires_grad, ::std::optional scale=::std::nullopt, ::std::optional num_splits_key=::std::nullopt, ::std::optional window_size=::std::nullopt, bool shared_storage_dqdkdv=false) { + return at::_ops::_efficient_attention_backward::call(grad_out_, query, key, value, bias, out, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, logsumexp, dropout_p, philox_seed, philox_offset, custom_mask_type, bias_requires_grad, scale, num_splits_key, window_size, shared_storage_dqdkdv); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0a007cbbe5018bcfe171da9f4c8acf0df4501cac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_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 & _efficientzerotensor_out_symint(c10::SymIntArrayRef size, at::Tensor & out); +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_cuda(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor _efficientzerotensor_meta_symint(c10::SymIntArrayRef 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/_embedding_bag_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c970fc5115c0f8a2d2bdfa79fa325ef11501a990 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, 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_outf(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); + +} // 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_bag_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3632a09dae71a07f71cdfb4ff4f072e4ccba08a6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _embedding_bag_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool, int64_t, 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::_embedding_bag"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +}} // 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h new file mode 100644 index 0000000000000000000000000000000000000000..e057b95ce6860292bb51526bcbb0d3bc2aad5016 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized.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::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, 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/_empty_affine_quantized_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc39f79a0f193addf7987315bffbc92ef2c68e4e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_affine_quantized_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 & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor & _empty_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor & _empty_affine_quantized_symint_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::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/_fake_quantize_learnable_per_channel_affine.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine.h new file mode 100644 index 0000000000000000000000000000000000000000..33a2d5bb1bdc023ed97735a00d2a4f93e5ff0c05 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine.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::_fake_quantize_learnable_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor +inline at::Tensor _fake_quantize_learnable_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0) { + return at::_ops::_fake_quantize_learnable_per_channel_affine::call(self, scale, zero_point, axis, quant_min, quant_max, grad_factor); +} + +// aten::_fake_quantize_learnable_per_channel_affine.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fake_quantize_learnable_per_channel_affine_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0) { + return at::_ops::_fake_quantize_learnable_per_channel_affine_out::call(self, scale, zero_point, axis, quant_min, quant_max, grad_factor, out); +} +// aten::_fake_quantize_learnable_per_channel_affine.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fake_quantize_learnable_per_channel_affine_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor, at::Tensor & out) { + return at::_ops::_fake_quantize_learnable_per_channel_affine_out::call(self, scale, zero_point, axis, quant_min, quant_max, grad_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/_fake_quantize_learnable_per_tensor_affine_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a6db336e66af045a5c3d2b5685468ae903b0128c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _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 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_learnable_per_tensor_affine_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f4198c299329cc9d6800a4cd2c57d0de94a16047 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _fake_quantize_learnable_per_tensor_affine { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fake_quantize_learnable_per_tensor_affine"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fake_quantize_learnable_per_tensor_affine(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor); +}; + +struct TORCH_API _fake_quantize_learnable_per_tensor_affine_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fake_quantize_learnable_per_tensor_affine"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fake_quantize_learnable_per_tensor_affine.out(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor, 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_c2c_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5663179fad82d3153a9a609db01eaf988c650d6b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_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 _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor _fft_c2c_symint(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); +TORCH_API at::Tensor & _fft_c2c_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_symint_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, 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/_foobar.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foobar.h new file mode 100644 index 0000000000000000000000000000000000000000..fc22902fdac65e6b1c32deb88c0fa5931fa82908 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foobar.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::_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor +inline at::Tensor _foobar(const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=true) { + return at::_ops::_foobar::call(self, arg1, arg2, arg3); +} + +// aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _foobar_out(at::Tensor & out, const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=true) { + return at::_ops::_foobar_out::call(self, arg1, arg2, arg3, out); +} +// aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _foobar_outf(const at::Tensor & self, bool arg1, bool arg2, bool arg3, at::Tensor & out) { + return at::_ops::_foobar_out::call(self, arg1, arg2, arg3, 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_acos_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_acos_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..954a2f86c02a5746c2993ef0bd0e396c8d318a63 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_acos_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_acos(at::TensorList self); +TORCH_API void _foreach_acos_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_acos_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_acos_(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_add_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..63a56f00f2f0477d7674a989b8180a41b72933f2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_add_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_add(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_add_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_add_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +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_out(at::TensorList out, at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_outf(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +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_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_add_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +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_out(at::TensorList out, at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_outf(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, at::TensorList out); +TORCH_API void _foreach_add_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=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/_foreach_addcmul.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcmul.h new file mode 100644 index 0000000000000000000000000000000000000000..132f3c8b1ea46a5e390f1f24d73d1d7322b04ad0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcmul.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_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] +inline ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1) { + return at::_ops::_foreach_addcmul_Scalar::call(self, tensor1, tensor2, value); +} + +// aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars) { + return at::_ops::_foreach_addcmul_ScalarList::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcmul.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] +inline ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { + return at::_ops::_foreach_addcmul_Tensor::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () +inline void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1) { + return at::_ops::_foreach_addcmul__Scalar::call(self, tensor1, tensor2, value); +} + +// aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () +inline void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars) { + return at::_ops::_foreach_addcmul__ScalarList::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcmul_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () +inline void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { + return at::_ops::_foreach_addcmul__Tensor::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcmul.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () +inline void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1) { + return at::_ops::_foreach_addcmul_Scalar_out::call(self, tensor1, tensor2, value, out); +} +// aten::_foreach_addcmul.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () +inline void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out) { + return at::_ops::_foreach_addcmul_Scalar_out::call(self, tensor1, tensor2, value, out); +} + +// aten::_foreach_addcmul.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars) { + return at::_ops::_foreach_addcmul_ScalarList_out::call(self, tensor1, tensor2, scalars, out); +} +// aten::_foreach_addcmul.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_addcmul_ScalarList_out::call(self, tensor1, tensor2, scalars, out); +} + +// aten::_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { + return at::_ops::_foreach_addcmul_Tensor_out::call(self, tensor1, tensor2, scalars, out); +} +// aten::_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out) { + return at::_ops::_foreach_addcmul_Tensor_out::call(self, tensor1, tensor2, 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_atan_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8b6f92b7d31f371e2c67738f7e133b088648aa88 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan_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_atan { + 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_atan"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_atan(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_atan_ { + 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_atan_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_atan_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_atan_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_atan"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_atan.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_ceil_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_ceil_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8eb672096e648a0f9fe9cbaaf2bf96491f1cd23a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_ceil { + 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_ceil"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_ceil(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_ceil_ { + 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_ceil_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_ceil_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_ceil_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_ceil"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_ceil.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_clamp_min.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_min.h new file mode 100644 index 0000000000000000000000000000000000000000..71735f403d00feee4e7d176a9ec03be7b8474d1e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_min.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_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_clamp_min(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_min_Scalar::call(self, scalar); +} + +// aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_clamp_min_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_min__Scalar::call(self, scalar); +} + +// aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_clamp_min(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_min_List::call(self, other); +} + +// aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_clamp_min_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_min__List::call(self, other); +} + +// aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_clamp_min(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_min_ScalarList::call(self, scalars); +} + +// aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_clamp_min_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_min__ScalarList::call(self, scalars); +} + +// aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_min_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_min_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_clamp_min_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_min_List_out::call(self, other, out); +} +// aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_min_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_clamp_min_List_out::call(self, other, out); +} + +// aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_min_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_min_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_clamp_min_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_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..eca5d87e4c757f946fc446cf4bb6df313f30b5c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_copy.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_copy_(Tensor(a!)[] self, Tensor[] src, bool non_blocking=False) -> () +inline void _foreach_copy_(at::TensorList self, at::TensorList src, bool non_blocking=false) { + return at::_ops::_foreach_copy_::call(self, src, non_blocking); +} + +// aten::_foreach_copy(Tensor[] self, Tensor[] src, bool non_blocking=False) -> Tensor[] self_out +inline ::std::vector _foreach_copy(at::TensorList self, at::TensorList src, bool non_blocking=false) { + return at::_ops::_foreach_copy::call(self, src, non_blocking); +} + +// aten::_foreach_copy.out(Tensor[] self, Tensor[] src, bool non_blocking=False, *, Tensor(a!)[] out) -> () +inline void _foreach_copy_out(at::TensorList out, at::TensorList self, at::TensorList src, bool non_blocking=false) { + return at::_ops::_foreach_copy_out::call(self, src, non_blocking, out); +} +// aten::_foreach_copy.out(Tensor[] self, Tensor[] src, bool non_blocking=False, *, Tensor(a!)[] out) -> () +inline void _foreach_copy_outf(at::TensorList self, at::TensorList src, bool non_blocking, at::TensorList out) { + return at::_ops::_foreach_copy_out::call(self, src, non_blocking, 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_cosh_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ee98911a1e757b549d52305bb3f6afe04e484200 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_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_cosh_slow(at::TensorList self); +TORCH_API void _foreach_cosh_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_cosh_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_cosh_cuda(at::TensorList self); +TORCH_API void foreach_tensor_cosh_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_erf_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..185bc138b31856ab2b1078b063c745da0f74eb80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_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_erf(at::TensorList self); +TORCH_API void _foreach_erf_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_erf_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_erf_(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_erf_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..892d6eea91628c3c98043082833b7ee4b36c710c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_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_erf_slow(at::TensorList self); +TORCH_API void _foreach_erf_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_erf_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_erf_cuda(at::TensorList self); +TORCH_API void foreach_tensor_erf_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_exp_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_exp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..22d032c7d5fb8327bf4007ab5b7009d69a5c97e8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_exp_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_exp { + 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_exp"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_exp(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_exp_ { + 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_exp_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_exp_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_exp_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_exp"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_exp.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_expm1.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_expm1.h new file mode 100644 index 0000000000000000000000000000000000000000..e7e09f65e5decfdaf0d0f974f4055798d1b1185e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_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::_foreach_expm1(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_expm1(at::TensorList self) { + return at::_ops::_foreach_expm1::call(self); +} + +// aten::_foreach_expm1_(Tensor(a!)[] self) -> () +inline void _foreach_expm1_(at::TensorList self) { + return at::_ops::_foreach_expm1_::call(self); +} + +// aten::_foreach_expm1.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_expm1_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_expm1_out::call(self, out); +} +// aten::_foreach_expm1.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_expm1_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_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/_foreach_floor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_floor.h new file mode 100644 index 0000000000000000000000000000000000000000..4c728d650899725365244926f0c29f209b6d096a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_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::_foreach_floor(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_floor(at::TensorList self) { + return at::_ops::_foreach_floor::call(self); +} + +// aten::_foreach_floor_(Tensor(a!)[] self) -> () +inline void _foreach_floor_(at::TensorList self) { + return at::_ops::_foreach_floor_::call(self); +} + +// aten::_foreach_floor.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_floor_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_floor_out::call(self, out); +} +// aten::_foreach_floor.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_floor_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_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/_foreach_frac_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_frac_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c6d3beac4b52617a48ddd33cb77303ead4bb48ad --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_frac_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_frac_slow(at::TensorList self); +TORCH_API void _foreach_frac_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_frac_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_frac_cuda(at::TensorList self); +TORCH_API void foreach_tensor_frac_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_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1bfb3a1b5a9a1e6b2b1a338098a470701035e1e8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_log2_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_log2(at::TensorList self); +TORCH_API void _foreach_log2_(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_max.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_max.h new file mode 100644 index 0000000000000000000000000000000000000000..0d01ab3297e1e2d836e56e255f572dd4f46a8216 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_max.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::_foreach_max(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_max(at::TensorList self) { + return at::_ops::_foreach_max::call(self); +} + +// aten::_foreach_max.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_max_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_max_out::call(self, out); +} +// aten::_foreach_max.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_max_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_max_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_maximum_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..684640fd16881011f0f96b75d95183dd27d9a549 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_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_min_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_maximum_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_clamp_min_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_min_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_clamp_min_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_min_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_maximum_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_clamp_min_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_min_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_clamp_min_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_min_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_maximum_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_clamp_min_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_clamp_min_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_clamp_min_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_maximum_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cafe1772bdea2468c44b9d0a95ee75c43b2482b9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_maximum_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_maximum_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_maximum"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_maximum.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_maximum__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_maximum_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_maximum_.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_maximum_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_maximum"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_maximum.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_maximum__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_maximum_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_maximum_.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_maximum_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_maximum"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_maximum.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_maximum__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_maximum_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_maximum_.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_maximum_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_maximum"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_maximum.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_maximum_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_maximum"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_maximum.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_maximum_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_maximum"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_maximum.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_minimum.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum.h new file mode 100644 index 0000000000000000000000000000000000000000..26a0821a087d3f3c11c23f936e9e3391776acf71 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum.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_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_minimum(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_minimum_Scalar::call(self, scalar); +} + +// aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_minimum_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_minimum__Scalar::call(self, scalar); +} + +// aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_minimum(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_minimum_List::call(self, other); +} + +// aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_minimum_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_minimum__List::call(self, other); +} + +// aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_minimum(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_minimum_ScalarList::call(self, scalars); +} + +// aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_minimum_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_minimum__ScalarList::call(self, scalars); +} + +// aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_minimum_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_minimum_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_minimum_List_out::call(self, other, out); +} +// aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_minimum_List_out::call(self, other, out); +} + +// aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_minimum_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_minimum_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_minimum_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..40d0ff50a781983a5442ee428401a57dc04b4ae1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum_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_minimum(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_minimum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_minimum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_minimum_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_minimum(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_minimum_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_minimum_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_minimum_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_minimum(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_minimum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_minimum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_minimum_(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_neg_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..707bdf0760ef7719099995449f7b6fa0ec870600 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg_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_neg_slow(at::TensorList self); +TORCH_API void _foreach_neg_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_neg_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_neg_cuda(at::TensorList self); +TORCH_API void foreach_tensor_neg_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_round.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round.h new file mode 100644 index 0000000000000000000000000000000000000000..60fd51d3d981c4314cc1184e011320956c65c145 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round.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_round(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_round(at::TensorList self) { + return at::_ops::_foreach_round::call(self); +} + +// aten::_foreach_round_(Tensor(a!)[] self) -> () +inline void _foreach_round_(at::TensorList self) { + return at::_ops::_foreach_round_::call(self); +} + +// aten::_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_round_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_round_out::call(self, out); +} +// aten::_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_round_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_round_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_rsqrt_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_native.h new file mode 100644 index 0000000000000000000000000000000000000000..33420e00b4c431836d62931479795464fe7180eb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt_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_rsqrt_slow(at::TensorList self); +TORCH_API void _foreach_rsqrt_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_rsqrt_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_rsqrt_cuda(at::TensorList self); +TORCH_API void foreach_tensor_rsqrt_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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sub_native.h new file mode 100644 index 0000000000000000000000000000000000000000..97d3e5110c45dd08f6bf5c1033dd393aaf8a799a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sub_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_sub_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_sub_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_sub_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_sub_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_sub_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_sub_list_kernel_slow(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_sub_List_out(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +TORCH_API void foreach_tensor_sub_list_kernel_slow_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_sub_list_kernel_cuda(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_sub_list_kernel_cuda_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_sub_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_sub_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_sub_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_sub_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_sub_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_tanh_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tanh_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..40cfc75af33913967edce9e26336f5e0ed4a838e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tanh_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_tanh(at::TensorList self); +TORCH_API void _foreach_tanh_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_tanh_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_tanh_(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/_functional_assert_scalar_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_scalar_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd4d5788b32de528c3fec6da0691aafda842c595 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_scalar_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 _functional_assert_scalar(const at::Scalar & self, c10::string_view assert_msg, const at::Tensor & dep_token); + +} // 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/_functional_sym_constrain_range.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range.h new file mode 100644 index 0000000000000000000000000000000000000000..25a0d03daf903021bb5f23bc2821dae88c866353 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range.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::_functional_sym_constrain_range(Scalar size, int? min, int? max, Tensor dep_token) -> Tensor +inline at::Tensor _functional_sym_constrain_range(const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token) { + return at::_ops::_functional_sym_constrain_range::call(size, min, max, dep_token); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_for_size_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7da4ed2a110304d8798264caaaf37a254565073c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_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 at::Tensor _functional_sym_constrain_range_for_size(const at::Scalar & size, ::std::optional min, ::std::optional max, 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/_fused_adagrad_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5abec11601627067d6f4eda53ed3edf0d0b9c6e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_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 void _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_(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 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/_fused_adamw_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04b8be9f3b72af3e65c659f31e373f4d5d0e1f2b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_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 ::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={}); +TORCH_API 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={}); +TORCH_API 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); +TORCH_API ::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={}); +TORCH_API 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={}); +TORCH_API 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); + +} // 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/_fused_adamw_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6be1e402c148ca2099a1f22bd36e020587cff212 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_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 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={}); +TORCH_API 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={}); + +} // 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/_fused_adamw_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d0d998544b51e588a2a273986cb720213bbfeeed --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_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,::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={}); +TORCH_API void _fused_adamw_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, at::TensorList out); +TORCH_API void _fused_adamw_kernel_cpu_(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={}); +TORCH_API void _fused_adamw_kernel_cuda_(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={}); +TORCH_API ::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={}); +TORCH_API void _fused_adamw_tensor_lr_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, at::TensorList out); +TORCH_API void _fused_adamw_kernel_cpu_(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={}); +TORCH_API void _fused_adamw_kernel_cuda_(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={}); +} // 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_dropout_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_dropout_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c4f8f63af664dc3a70bd64f511eed288211ab042 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_dropout_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 _fused_dropout_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +TORCH_API ::std::tuple _fused_dropout_outf(const at::Tensor & self, double p, ::std::optional generator, 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/_fused_moving_avg_obs_fq_helper.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..b7554bb65609d1340ec75710f61c5d8354f64287 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper.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::_fused_moving_avg_obs_fq_helper(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask) +inline ::std::tuple _fused_moving_avg_obs_fq_helper(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false) { + return at::_ops::_fused_moving_avg_obs_fq_helper::call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); +} + +// aten::_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!)) +inline ::std::tuple _fused_moving_avg_obs_fq_helper_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false) { + return at::_ops::_fused_moving_avg_obs_fq_helper_out::call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant, out0, out1); +} +// aten::_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!)) +inline ::std::tuple _fused_moving_avg_obs_fq_helper_outf(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_fused_moving_avg_obs_fq_helper_out::call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant, out0, out1); +} + +// aten::_fused_moving_avg_obs_fq_helper_functional(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor running_min, Tensor running_max, Tensor scale, Tensor zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask, Tensor running_min_out, Tensor running_max_out, Tensor scale_out, Tensor zero_point_out) +inline ::std::tuple _fused_moving_avg_obs_fq_helper_functional(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false) { + return at::_ops::_fused_moving_avg_obs_fq_helper_functional::call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_moving_avg_obs_fq_helper_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b4a3db9e50bdc12d5039ca53adf310ff47137ce5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_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 ::std::tuple _fused_moving_avg_obs_fq_helper_functional(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false); +TORCH_API ::std::tuple _fused_moving_avg_obs_fq_helper_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false); +TORCH_API ::std::tuple _fused_moving_avg_obs_fq_helper_outf(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, 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/_fused_moving_avg_obs_fq_helper_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1e3364015a9cd8ba82c928cc433fe8a8b0de1af --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_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 _fused_moving_avg_obs_fq_helper { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, double, int64_t, int64_t, int64_t, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_moving_avg_obs_fq_helper"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_moving_avg_obs_fq_helper(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant); +}; + +struct TORCH_API _fused_moving_avg_obs_fq_helper_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, double, int64_t, int64_t, 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::_fused_moving_avg_obs_fq_helper"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, at::Tensor & out0, at::Tensor & out1); +}; + +struct TORCH_API _fused_moving_avg_obs_fq_helper_functional { + 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 &, double, int64_t, int64_t, int64_t, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_moving_avg_obs_fq_helper_functional"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_moving_avg_obs_fq_helper_functional(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor running_min, Tensor running_max, Tensor scale, Tensor zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask, Tensor running_min_out, Tensor running_max_out, Tensor scale_out, Tensor zero_point_out)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant); +}; + +}} // 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_sgd.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd.h new file mode 100644 index 0000000000000000000000000000000000000000..730d1b8fb7395d274c380ed3e005029f60b1cab3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd.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_sgd_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] momentum_buffer_list, *, float weight_decay, float momentum, float lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_sgd_(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_sgd_::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf); +} + +// aten::_fused_sgd_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] momentum_buffer_list, *, float weight_decay, float momentum, Tensor lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_sgd_(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_sgd__tensor_lr::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf); +} + +// aten::_fused_sgd.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] momentum_buffer_list, *, float weight_decay, float momentum, float lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_sgd_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_sgd_out::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf, out); +} +// aten::_fused_sgd.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] momentum_buffer_list, *, float weight_decay, float momentum, float lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_sgd_outf(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_sgd_out::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf, out); +} + +// aten::_fused_sgd(Tensor[] self, Tensor[] grads, Tensor[] momentum_buffer_list, *, float weight_decay, float momentum, float lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] momentum_buffer_list_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_sgd(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_sgd::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf); +} + +// aten::_fused_sgd.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] momentum_buffer_list, *, float weight_decay, float momentum, Tensor lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_sgd_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_sgd_tensor_lr_out::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf, out); +} +// aten::_fused_sgd.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] momentum_buffer_list, *, float weight_decay, float momentum, Tensor lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_sgd_outf(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_sgd_tensor_lr_out::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, grad_scale, found_inf, out); +} + +// aten::_fused_sgd.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] momentum_buffer_list, *, float weight_decay, float momentum, Tensor lr, float dampening, bool nesterov, bool maximize, bool is_first_step, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] momentum_buffer_list_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_sgd(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_sgd_tensor_lr::call(self, grads, momentum_buffer_list, weight_decay, momentum, lr, dampening, nesterov, maximize, is_first_step, 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_sgd_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb798e1fe01ec608a9d462b2c52bdc59e06df907 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd_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 ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_sgd(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_outf(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_sgd(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_outf(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale, const ::std::optional & found_inf, 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/_fw_primal_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c5317f42cc9d679a3e91d3351e1d0d2b3fd68d38 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_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 _fw_primal_copy { + 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::_fw_primal_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fw_primal_copy(Tensor self, int level) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t level); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t level); +}; + +struct TORCH_API _fw_primal_copy_out { + using schema = 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::_fw_primal_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t level, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t level, 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/_grid_sampler_2d_cpu_fallback_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eb484aa3d936a52c34da147a3a5eadc7bb2449ee --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_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 _grid_sampler_2d_cpu_fallback(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +TORCH_API at::Tensor & _grid_sampler_2d_cpu_fallback_out(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, 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/_has_compatible_shallow_copy_type.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type.h new file mode 100644 index 0000000000000000000000000000000000000000..fef3db047e4912ecc189db1c8524793584edd6a0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type.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::_has_compatible_shallow_copy_type(Tensor self, Tensor from) -> bool +inline bool _has_compatible_shallow_copy_type(const at::Tensor & self, const at::Tensor & from) { + return at::_ops::_has_compatible_shallow_copy_type::call(self, from); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compatible_shallow_copy_type_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5afe88bbe083f467afefcd9f601f9ba5e51e8824 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_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 _has_compatible_shallow_copy_type(const at::Tensor & self, const at::Tensor & from); + +} // 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/_histogramdd_bin_edges_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..725d6adf13d2e66e6a532849448e749a88125d77 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_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 void _histogramdd_bin_edges_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API void _histogramdd_bin_edges_outf(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, 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/_histogramdd_bin_edges_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_native.h new file mode 100644 index 0000000000000000000000000000000000000000..df1d85cdd076a31b8d13eebb34b824e4ed763a06 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_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 _histogramdd_bin_edges_out(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::TensorList out); +TORCH_API ::std::vector histogramdd_bin_edges(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=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/_histogramdd_from_bin_cts_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9938b46cf857828bc2a10ace5113a1176c30d425 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_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 & _histogramdd_from_bin_cts_out(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::Tensor & out); +TORCH_API at::Tensor _histogramdd(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=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/_index_put_impl_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c43dafd20205031389d9ef3ba757490d5acfc57 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_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 _index_put_impl(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); +TORCH_API at::Tensor & _index_put_impl_out(at::Tensor & out, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); +TORCH_API at::Tensor & _index_put_impl_outf(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, 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/_index_put_impl_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_native.h new file mode 100644 index 0000000000000000000000000000000000000000..971ff3234b07152888d5a378fa3c466b0ad1b3a5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_index_put_impl_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 _index_put_impl(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); +TORCH_API at::Tensor & _index_put_impl_out(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out); +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); +TORCH_API at::Tensor & _index_put_impl_quantized_cpu_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); +TORCH_API at::Tensor & _index_put_impl_quantized_cuda_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=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/_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..f9e024dffaa4ad02e0aae6dd8c542e60d8589533 --- /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/_is_all_true_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_is_all_true_native.h new file mode 100644 index 0000000000000000000000000000000000000000..399b838cea5b5e6449b798042a41462b375f01a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_is_all_true_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 _is_all_true(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_any_true_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_is_any_true_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ec11d1e8f320dcbffc71f4cfbf1213614773e36 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_is_any_true_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 _is_any_true(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/_is_zerotensor_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_is_zerotensor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64209bf222872ac6bfef51dc84c9e63472adc7c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_is_zerotensor_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 _is_zerotensor(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/_jagged_to_padded_dense_forward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_jagged_to_padded_dense_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c05239e6b66fe6cd86243d07811c4f22c6d7819d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_jagged_to_padded_dense_forward_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 _jagged_to_padded_dense_forward(const at::Tensor & values, at::TensorList offsets, at::IntArrayRef max_lengths, double padding_value=0.0); +TORCH_API at::Tensor _jagged_to_padded_dense_forward_symint(const at::Tensor & values, at::TensorList offsets, c10::SymIntArrayRef max_lengths, double padding_value=0.0); + +} // 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/_lazy_clone.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_lazy_clone.h new file mode 100644 index 0000000000000000000000000000000000000000..4c5d36b4c3d4e54f37afb0cbca6cd9a47cb866ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_lazy_clone.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::_lazy_clone(Tensor self) -> Tensor +inline at::Tensor _lazy_clone(const at::Tensor & self) { + return at::_ops::_lazy_clone::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/_linalg_det_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..098b690f1b6ea22a5833a14248f2d1185a5c2b51 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_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_det : public at::impl::MetaBase { + + + void meta(const at::Tensor & A); +}; + +} // 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_det_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..036498f838cf966012d6bfb9c576ae4352ff7781 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_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_det(const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_outf(const at::Tensor & A, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots); + +} // 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_eigh_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eb81dac129b723aa8e4b4a8e972ded1c25150f67 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_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_eigh_out : public at::meta::structured__linalg_eigh { +void impl(const at::Tensor & A, c10::string_view UPLO, bool compute_v, const at::Tensor & eigenvalues, const at::Tensor & eigenvectors); +}; +} // 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_eigvals_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..03250effef9c1693f4f0b24a9d7f39a01b989b92 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_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 _linalg_eigvals(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/_linalg_solve_ex_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c0ae66a95bedcd6f432ff9e0dc6cc39286ad7b8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_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_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); +TORCH_API ::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); +TORCH_API ::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); + +} // 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_solve_ex_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..69b60daef93601c8824e5e29dc7375c4e3c8c93e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_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_solve_ex : public at::impl::MetaBase { + + + void meta(const at::Tensor & A, const at::Tensor & B, bool left, 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/_log_softmax_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e1f3bb3a3e3847e1728c09fd95ff7e24ec59c25c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_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(const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _log_softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _log_softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, 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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9cd911733d20e9fe8e36b40bf70ad1803b7b322c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_log_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 _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::_log_softmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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 _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::_log_softmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_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/_logcumsumexp_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_logcumsumexp_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fbb1ae38cead8c553de547dd03b3c818d32491d1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_logcumsumexp_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 _logcumsumexp(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & _logcumsumexp_out(at::Tensor & out, const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & _logcumsumexp_outf(const at::Tensor & self, 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/_lu_with_info_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_lu_with_info_native.h new file mode 100644 index 0000000000000000000000000000000000000000..39e6f045933bb9c1be82740af69084798870f197 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_lu_with_info_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 _lu_with_info(const at::Tensor & self, bool pivot=true, bool check_errors=true); +} // 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/_lu_with_info_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_lu_with_info_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..258eee8586d17ea83ec2c678e16f8c3a4e7f6435 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_lu_with_info_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 _lu_with_info { + using schema = ::std::tuple (const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_lu_with_info"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_lu_with_info(Tensor self, bool pivot=True, bool check_errors=True) -> (Tensor LU, Tensor pivots, Tensor info)"; + static ::std::tuple call(const at::Tensor & self, bool pivot, bool check_errors); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool pivot, bool check_errors); +}; + +}} // 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/_make_dep_token_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2d1b0a896d6427e58f82979b9f250a639edb0f54 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_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 _make_dep_token(at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor _make_dep_token(::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + +} // 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/_make_dual_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..de5a7f1b1edb8c32f6fad11106872569a5cf77a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_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::_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor +inline at::Tensor _make_dual_copy(const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual_copy::call(primal, tangent, level); +} + +// aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_dual_copy_out(at::Tensor & out, const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual_copy_out::call(primal, tangent, level, out); +} +// aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_dual_copy_outf(const at::Tensor & primal, const at::Tensor & tangent, int64_t level, at::Tensor & out) { + return at::_ops::_make_dual_copy_out::call(primal, tangent, level, 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/_mixed_dtypes_linear.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mixed_dtypes_linear.h new file mode 100644 index 0000000000000000000000000000000000000000..21e633af0ab796f16987e34e67e0a8a29b6a924a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mixed_dtypes_linear.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::_mixed_dtypes_linear(Tensor input, Tensor weight, Tensor scale, *, Tensor? bias=None, str? activation=None) -> Tensor +inline at::Tensor _mixed_dtypes_linear(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & scale, const ::std::optional & bias={}, ::std::optional activation=::std::nullopt) { + return at::_ops::_mixed_dtypes_linear::call(input, weight, scale, bias, activation); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8a8c523c6db3f6dd244d2004eaef721a5d53494f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_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 _mps_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, 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"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_mps_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef 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, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API _mps_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, 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"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_mps_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(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); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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 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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0f362e1fd4474baab9361d82547c071e00a592c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_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 + + +namespace at { +namespace native { +TORCH_API ::std::tuple _native_batch_norm_legit_functional(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple _batch_norm_legit_cpu_out(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 _batch_norm_legit_cpu(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 _batch_norm_legit_cuda_out(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 _batch_norm_legit_cuda(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 _mkldnn_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 _batch_norm_legit_no_stats_cpu(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps); +TORCH_API ::std::tuple _batch_norm_legit_no_stats_cpu_out(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); +TORCH_API ::std::tuple _batch_norm_legit_no_stats_cuda(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps); +TORCH_API ::std::tuple _batch_norm_legit_no_stats_cuda_out(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); +TORCH_API ::std::tuple _mkldnn_batch_norm_legit_no_stats(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, 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_batch_norm_legit_no_training.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_no_training.h new file mode 100644 index 0000000000000000000000000000000000000000..516a676be167a8cffbaecbe7ac07a2d7ac127b26 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_no_training.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_batch_norm_legit_no_training(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _native_batch_norm_legit_no_training(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps) { + return at::_ops::_native_batch_norm_legit_no_training::call(input, weight, bias, running_mean, running_var, momentum, eps); +} + +// aten::_native_batch_norm_legit_no_training.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(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _native_batch_norm_legit_no_training_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps) { + return at::_ops::_native_batch_norm_legit_no_training_out::call(input, weight, bias, running_mean, running_var, momentum, eps, out0, out1, out2); +} +// aten::_native_batch_norm_legit_no_training.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(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _native_batch_norm_legit_no_training_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::_native_batch_norm_legit_no_training_out::call(input, weight, bias, running_mean, running_var, momentum, eps, 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/_native_batch_norm_legit_no_training_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_no_training_native.h new file mode 100644 index 0000000000000000000000000000000000000000..32ed3eea12574c983537f77ec4732f3fe621e3a6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_no_training_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_legit_no_training(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_no_training_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +} // 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_multi_head_attention.h new file mode 100644 index 0000000000000000000000000000000000000000..42c666dedb0150d8bf1de03969967354d2f102d9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_native_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::_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) +inline ::std::tuple _native_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={}, bool need_weights=true, bool average_attn_weights=true, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_native_multi_head_attention::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type); +} + +// aten::_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!)) +inline ::std::tuple _native_multi_head_attention_out(at::Tensor & out0, at::Tensor & out1, 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) { + return at::_ops::_native_multi_head_attention_out::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type, out0, out1); +} +// aten::_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!)) +inline ::std::tuple _native_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, bool need_weights, bool average_attn_weights, ::std::optional mask_type, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_native_multi_head_attention_out::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type, 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/_neg_view_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..4fcf945ebb2d08fc0a81334285a6322110490770 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_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::_neg_view_copy(Tensor self) -> Tensor +inline at::Tensor _neg_view_copy(const at::Tensor & self) { + return at::_ops::_neg_view_copy::call(self); +} + +// aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _neg_view_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_neg_view_copy_out::call(self, out); +} +// aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _neg_view_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_neg_view_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/_nested_from_padded_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5dd1c75be3c25a6fe425b0a4bb1068139f167beb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_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 & _nested_from_padded_out(at::Tensor & out, const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213=false); +TORCH_API at::Tensor & _nested_from_padded_outf(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213, 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/_nested_from_padded_tensor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..2c989870f1192167856dc6e43093982c49d5142d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_tensor.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::_nested_from_padded_tensor(Tensor padded, Tensor offsets, Tensor dummy, int ragged_idx=1, Tensor? min_seqlen=None, Tensor? max_seqlen=None, SymInt? sum_S=None) -> Tensor +inline at::Tensor _nested_from_padded_tensor(const at::Tensor & padded, const at::Tensor & offsets, const at::Tensor & dummy, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}, ::std::optional sum_S=::std::nullopt) { + return at::_ops::_nested_from_padded_tensor::call(padded, offsets, dummy, ragged_idx, min_seqlen, max_seqlen, sum_S.has_value() ? ::std::make_optional(c10::SymInt(*sum_S)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor _nested_from_padded_tensor(const at::Tensor & padded, const at::Tensor & offsets, const at::Tensor & dummy, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}, ::std::optional sum_S=::std::nullopt) { + return at::_ops::_nested_from_padded_tensor::call(padded, offsets, dummy, ragged_idx, min_seqlen, max_seqlen, sum_S.has_value() ? ::std::make_optional(c10::SymInt(*sum_S)) : ::std::nullopt); + } +} + +// aten::_nested_from_padded_tensor(Tensor padded, Tensor offsets, Tensor dummy, int ragged_idx=1, Tensor? min_seqlen=None, Tensor? max_seqlen=None, SymInt? sum_S=None) -> Tensor +inline at::Tensor _nested_from_padded_tensor_symint(const at::Tensor & padded, const at::Tensor & offsets, const at::Tensor & dummy, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}, ::std::optional sum_S=::std::nullopt) { + return at::_ops::_nested_from_padded_tensor::call(padded, offsets, dummy, ragged_idx, min_seqlen, max_seqlen, sum_S); +} +namespace symint { + template >> + at::Tensor _nested_from_padded_tensor(const at::Tensor & padded, const at::Tensor & offsets, const at::Tensor & dummy, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}, ::std::optional sum_S=::std::nullopt) { + return at::_ops::_nested_from_padded_tensor::call(padded, offsets, dummy, ragged_idx, min_seqlen, max_seqlen, sum_S); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_tensor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_tensor_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_from_padded_tensor_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_jagged_dummy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_jagged_dummy.h new file mode 100644 index 0000000000000000000000000000000000000000..6047509cc8d5f635acb7c4e4ca748f4fb8d54d9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_jagged_dummy.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_jagged_dummy(Tensor any) -> Tensor +inline at::Tensor _nested_get_jagged_dummy(const at::Tensor & any) { + return at::_ops::_nested_get_jagged_dummy::call(any); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_offsets_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_offsets_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_offsets_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_tensor_from_mask_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4bf386651e4f44c12842a429295154704e609ace --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_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 _nested_tensor_from_mask(const at::Tensor & t, const at::Tensor & mask, bool mask_check=true); + +} // 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/_nested_tensor_from_mask_left_aligned_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..896df0776381274c50e1747a7c7cc5478df3e3a2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_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 _nested_tensor_from_mask_left_aligned { + using schema = bool (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::_nested_tensor_from_mask_left_aligned"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nested_tensor_from_mask_left_aligned(Tensor t, Tensor mask) -> bool"; + static bool call(const at::Tensor & t, const at::Tensor & mask); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & t, const at::Tensor & mask); +}; + +}} // 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_tensor_storage_offsets_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3eb34a5382c1c17cf8865a862ff191518a84bfdb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_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 & _nested_tensor_storage_offsets_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & _nested_tensor_storage_offsets_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/_nested_tensor_storage_offsets_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e06bb6935a48845f13792602318b2d00e1b2879a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_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_tensor_storage_offsets_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _nested_tensor_storage_offsets(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/_nested_tensor_strides.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides.h new file mode 100644 index 0000000000000000000000000000000000000000..777bd1c9e76b5f432240ded6e36832574a7318ae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides.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::_nested_tensor_strides.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_strides_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_nested_tensor_strides_out::call(self, out); +} +// aten::_nested_tensor_strides.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_strides_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_nested_tensor_strides_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/_nested_tensor_strides_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..78d5d11e01e166d3f668d7e291aa5fd1491126a7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_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_tensor_strides { + 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::_nested_tensor_strides"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nested_tensor_strides(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 _nested_tensor_strides_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::_nested_tensor_strides"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_nested_tensor_strides.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/_nested_view_from_buffer.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer.h new file mode 100644 index 0000000000000000000000000000000000000000..aa0046c62684103032913f4d240a009502822e76 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer.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_view_from_buffer(Tensor(a) self, Tensor nested_size, Tensor nested_strides, Tensor offsets) -> Tensor(a) +inline at::Tensor _nested_view_from_buffer(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets) { + return at::_ops::_nested_view_from_buffer::call(self, nested_size, nested_strides, offsets); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_buffer_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..ecf046ca89230a2f206a61fe15310a2ae93acd12 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_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::_nested_view_from_buffer_copy(Tensor self, Tensor nested_size, Tensor nested_strides, Tensor offsets) -> Tensor +inline at::Tensor _nested_view_from_buffer_copy(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets) { + return at::_ops::_nested_view_from_buffer_copy::call(self, nested_size, nested_strides, offsets); +} + +// aten::_nested_view_from_buffer_copy.out(Tensor self, Tensor nested_size, Tensor nested_strides, Tensor offsets, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_view_from_buffer_copy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets) { + return at::_ops::_nested_view_from_buffer_copy_out::call(self, nested_size, nested_strides, offsets, out); +} +// aten::_nested_view_from_buffer_copy.out(Tensor self, Tensor nested_size, Tensor nested_strides, Tensor offsets, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_view_from_buffer_copy_outf(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets, at::Tensor & out) { + return at::_ops::_nested_view_from_buffer_copy_out::call(self, nested_size, nested_strides, offsets, 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/_nested_view_from_buffer_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bcb188d9338445ed706c80b021e868e76776ba0a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_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 & _nested_view_from_buffer_copy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets); +TORCH_API at::Tensor & _nested_view_from_buffer_copy_outf(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets, 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/_nested_view_from_buffer_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca0d7d338144664c875205c0ec756321270d6777 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_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 _nested_view_from_buffer_copy(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets); + +} // 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/_nnz.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnz.h new file mode 100644 index 0000000000000000000000000000000000000000..d105722242ac7b04cc3b2ca5e5fa32d0646b155e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_nnz.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/_pack_padded_sequence_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9dfdb268c8eb787e0907dc6c78dafbba2a91fe2d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_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 _pack_padded_sequence(const at::Tensor & input, const at::Tensor & lengths, bool batch_first); +TORCH_API ::std::tuple _pack_padded_sequence_out(const at::Tensor & input, const at::Tensor & lengths, bool batch_first, at::Tensor & out0, at::Tensor & out1); +} // 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_enum_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_enum_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72203b20c81d8542936bf11648d97e3c93d1bf25 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_enum_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_enum(const at::Tensor & self, at::IntArrayRef pad, int64_t mode, ::std::optional value=::std::nullopt); +TORCH_API at::Tensor _pad_enum_symint(const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, ::std::optional value=::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/_padded_dense_to_jagged_forward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39dc5d4b1c0005e086b6150dcfda8322a9dadbc2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_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 _padded_dense_to_jagged_forward(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L=::std::nullopt); +TORCH_API at::Tensor _padded_dense_to_jagged_forward_symint(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L=::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/_pdist_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..420d40dde310bdc6cd8873d150200fe3ff315d0b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_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 _pdist_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pdist_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_pdist_backward(Tensor grad, Tensor self, float p, Tensor pdist) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, double p, const at::Tensor & pdist); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, double p, const at::Tensor & pdist); +}; + +struct TORCH_API _pdist_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, double, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_pdist_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_pdist_backward.out(Tensor grad, Tensor self, float p, Tensor pdist, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & self, double p, const at::Tensor & pdist, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, double p, const at::Tensor & pdist, 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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6fc74a5157fe961a14f205ee13f5065d01156107 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory_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 _pin_memory(const at::Tensor & self, ::std::optional device=::std::nullopt); +TORCH_API at::Tensor & _pin_memory_out(const at::Tensor & self, ::std::optional device, at::Tensor & out); +TORCH_API at::Tensor _pin_memory_nested(const at::Tensor & self, ::std::optional device=::std::nullopt); +TORCH_API at::Tensor _pin_memory_sparse_coo(const at::Tensor & self, ::std::optional device=::std::nullopt); +TORCH_API at::Tensor _pin_memory_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/_prelu_kernel_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..195251802866d69d8612fa0aa7868056edbde949 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_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 _prelu_kernel(const at::Tensor & self, 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/_prelu_kernel_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e287d30657044606505c8058c73aa3390e2d1fcc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_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 _prelu_kernel(const at::Tensor & self, const at::Tensor & 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/_propagate_xla_data_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4e0fba81562e6e1592792e7ab73eeec9105b3b00 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_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 _propagate_xla_data { + using schema = void (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::_propagate_xla_data"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_propagate_xla_data(Tensor input, Tensor output) -> ()"; + static void call(const at::Tensor & input, const at::Tensor & output); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, 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/_remove_batch_dim_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_remove_batch_dim_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a05658149cbd53cf03a980ed9737ea1d33ccc71a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_remove_batch_dim_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 _remove_batch_dim { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::SymInt, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_remove_batch_dim"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_remove_batch_dim(Tensor self, int level, SymInt batch_size, int out_dim) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t level, c10::SymInt batch_size, int64_t out_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t level, c10::SymInt batch_size, int64_t out_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/_reshape_alias_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_alias_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..dad749a30247d7d39e4e855d8b60fc8f556b30b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_reshape_alias_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 & _reshape_alias_copy_out_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor _reshape_alias_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); +} // 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_output_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_resize_output_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..df4f6afed638cf175979f02fadcc6b150a3204c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_resize_output_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 const at::Tensor & _resize_output_(const at::Tensor & self, at::IntArrayRef size, at::Device device); +TORCH_API const at::Tensor & _resize_output__symint(const at::Tensor & self, c10::SymIntArrayRef size, at::Device device); + +} // 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/_resize_output_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_resize_output_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fcfde7917d6ce746f785e66261a7a542fe08dbf2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_resize_output_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_output_ { + using schema = const at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Device); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_resize_output_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_resize_output_(Tensor(a!) self, SymInt[] size, Device device) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, at::Device device); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Device device); +}; + +struct TORCH_API _resize_output_out { + using schema = const at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Device, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_resize_output"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_resize_output.out(Tensor self, SymInt[] size, Device device, *, Tensor(a!) out) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, at::Device device, const at::Tensor & out); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Device device, const at::Tensor & out); +}; + +struct TORCH_API _resize_output { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, at::Device); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_resize_output"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_resize_output(Tensor self, SymInt[] size, Device device) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, at::Device device); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Device device); +}; + +}} // 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_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..574adc7bc02edd9f9023ca45901d894d3241020a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_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 _sample_dirichlet(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/_saturate_weight_to_fp16_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bc26ffecdc37609ffaf1370573657a165e098ff0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16_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 _saturate_weight_to_fp16(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/_scaled_dot_product_attention_math_for_mps.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_for_mps.h new file mode 100644 index 0000000000000000000000000000000000000000..04e43332183bbe492ff830294f6e9ce123c06668 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_for_mps.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_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) +inline ::std::tuple _scaled_dot_product_attention_math_for_mps(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) { + return at::_ops::_scaled_dot_product_attention_math_for_mps::call(query, key, value, attn_mask, dropout_p, is_causal, dropout_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/_scaled_dot_product_attention_math_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2459edca7d49ee8695e27231149863decd4f49d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_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 { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, double, bool, const ::std::optional &, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_scaled_dot_product_attention_math"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_scaled_dot_product_attention_math(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, bool enable_gqa=False) -> (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, bool enable_gqa); + 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, bool enable_gqa); +}; + +}} // 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention.h new file mode 100644 index 0000000000000000000000000000000000000000..303e4dac4b34cd62460481f09d4cc66aba2ad3f3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_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_cudnn_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, 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 _scaled_dot_product_cudnn_attention(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, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_scaled_dot_product_cudnn_attention::call(query, key, value, attn_bias, 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/_scaled_dot_product_efficient_attention_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d338ae8446a49c2ffa556cc8196c853a73dbdeb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_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 _scaled_dot_product_efficient_attention_backward(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & attn_bias, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & philox_seed, const at::Tensor & philox_offset, double dropout_p, ::std::array grad_input_mask, bool is_causal=false, ::std::optional scale=::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/_scaled_dot_product_fused_attention_overrideable_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..63fe4d65fc13b0f0e46be2125e3062a5adb6cced --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_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 ::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 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/_scaled_grouped_mm_v2.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm_v2.h new file mode 100644 index 0000000000000000000000000000000000000000..0991efcda57d20e5d929e6847911f7c4ae2d91a2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_grouped_mm_v2.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_v2(Tensor self, Tensor mat2, Tensor[] scale_a, int[] recipe_a, int[] swizzle_a, Tensor[] scale_b, int[] recipe_b, int[] swizzle_b, Tensor? offs=None, Tensor? bias=None, ScalarType? out_dtype=None, int[] contraction_dim=[], bool use_fast_accum=False) -> Tensor +inline at::Tensor _scaled_grouped_mm_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) { + return at::_ops::_scaled_grouped_mm_v2::call(self, mat2, scale_a, recipe_a, swizzle_a, scale_b, recipe_b, swizzle_b, offs, bias, out_dtype, contraction_dim, 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/_segment_reduce_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_segment_reduce_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aa6ca7853f6960e3ce4b51e7f3cb61480a017899 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_segment_reduce_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 & _segment_reduce_backward_out(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths, const ::std::optional & offsets, int64_t axis, const ::std::optional & initial, at::Tensor & out); +TORCH_API at::Tensor _segment_reduce_backward_kernel(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths={}, const ::std::optional & offsets={}, int64_t axis=0, const ::std::optional & initial=::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/_slow_conv2d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..4567844db6bdc2a2be0ea3f9eadebff8e334f02a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_backward.h @@ -0,0 +1,141 @@ +#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_conv2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), grad_input, grad_weight, grad_bias); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), grad_input, grad_weight, grad_bias); + } +} + +// aten::_slow_conv2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), grad_input, grad_weight, grad_bias); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), grad_input, grad_weight, grad_bias); + } +} + +// aten::_slow_conv2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_symint_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, kernel_size, stride, padding, grad_input, grad_weight, grad_bias); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, kernel_size, stride, padding, grad_input, grad_weight, grad_bias); + } +} + +// aten::_slow_conv2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, kernel_size, stride, padding, grad_input, grad_weight, grad_bias); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias) { + return at::_ops::_slow_conv2d_backward_grad_input::call(grad_output, self, weight, kernel_size, stride, padding, grad_input, grad_weight, grad_bias); + } +} + +// aten::_slow_conv2d_backward.output_mask(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) +inline ::std::tuple _slow_conv2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output_mask); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output_mask); + } +} + +// aten::_slow_conv2d_backward.output_mask(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) +inline ::std::tuple _slow_conv2d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask::call(grad_output, self, weight, kernel_size, stride, padding, output_mask); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask::call(grad_output, self, weight, kernel_size, stride, padding, output_mask); + } +} + +// aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output_mask, out0, out1, out2); + } +} + +// aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, c10::fromIntArrayRefSlow(kernel_size), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output_mask, out0, out1, out2); + } +} + +// aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, kernel_size, stride, padding, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, kernel_size, stride, padding, output_mask, out0, out1, out2); + } +} + +// aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple _slow_conv2d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, kernel_size, stride, padding, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::_slow_conv2d_backward_output_mask_out::call(grad_output, self, weight, kernel_size, stride, padding, output_mask, 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/_slow_conv2d_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9e985b2b118122b807fb0d9c188b367d4e24bac0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_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 _slow_conv2d_backward_grad_input { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, 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::_slow_conv2d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "_slow_conv2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); +}; + +struct TORCH_API _slow_conv2d_backward_output_mask { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_slow_conv2d_backward"; + static constexpr const char* overload_name = "output_mask"; + static constexpr const char* schema_str = "_slow_conv2d_backward.output_mask(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask); +}; + +struct TORCH_API _slow_conv2d_backward_output_mask_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, ::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::_slow_conv2d_backward"; + static constexpr const char* overload_name = "output_mask_out"; + static constexpr const char* schema_str = "_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, SymInt[2] kernel_size, SymInt[2] stride, SymInt[2] padding, 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_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::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/_sobol_engine_draw.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_draw.h new file mode 100644 index 0000000000000000000000000000000000000000..e4d8e017ed522b17a79a8cb80e2b77e9d3c95d31 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_draw.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_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor) +inline ::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) { + return at::_ops::_sobol_engine_draw::call(quasi, n, sobolstate, dimension, num_generated, 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/_sobol_engine_scramble_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_scramble_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d8cfd4bdc29c94fadac939b98ee543230dcae77a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sobol_engine_scramble_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 _sobol_engine_scramble_ { + using schema = at::Tensor & (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::_sobol_engine_scramble_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sobol_engine_scramble_(Tensor(a!) self, Tensor ltm, int dimension) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & ltm, int64_t dimension); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & ltm, int64_t dimension); +}; + +}} // 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/_softmax_backward_data_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f1117ebdcb3c7e13d3470e9ced1da5a770e8105 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_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 _softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_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/_softmax_backward_data_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..259fe85b38390543e546c5ff7f024e324b33a825 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_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 _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 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/_softmax_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..05f132037ed7b489bced4f50558440a0de2fc42d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_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 _softmax(const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, 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/_softmax_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e91c3b34ac85d32ac491001006c630131ee07691 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_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 _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::_softmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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 _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::_softmax"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_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_addmm_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6f469286fb6a7a103f38475c91fb5a90e057e06b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_addmm_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 _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(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); +TORCH_API 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); + +} // 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_broadcast_to_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..fdf1db615883ae6c81c08eb5e2124dc5e904f836 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_broadcast_to_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::_sparse_broadcast_to_copy(Tensor self, int[] size) -> Tensor +inline at::Tensor _sparse_broadcast_to_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::_sparse_broadcast_to_copy::call(self, size); +} + +// aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_broadcast_to_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::_sparse_broadcast_to_copy_out::call(self, size, out); +} +// aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_broadcast_to_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::_sparse_broadcast_to_copy_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/_sparse_bsc_tensor_unsafe_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e8d792e2c606dbedf735991c15b314792ba8a1c9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_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_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={}); +} // 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_bsr_tensor_unsafe_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsr_tensor_unsafe_native.h new file mode 100644 index 0000000000000000000000000000000000000000..76860e3d42567c64086fd0fa331b639a49d4ef2b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsr_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_bsr_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={}); +} // 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_compressed_tensor_unsafe_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d65d62c71eb7e8d854ba2bae1bd3bf9ba5b2f2a1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_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_unsafe { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const 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::_sparse_compressed_tensor_unsafe"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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 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_csc_tensor_unsafe_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02173c1cc8e2586d5f60012cba9132885f8c80c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_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 _sparse_csc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}); +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 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_csr_prod_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_prod_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..690c4fa96374d1ae0e5d3c87ce5cf49542bb38aa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_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 & _sparse_csr_prod_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & _sparse_csr_prod_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::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/_sparse_csr_sum_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_sum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6ce3fbb1ffa473754eba03d2bd0948525ee32355 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_sum_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_csr_sum_dim_dtype_out(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor _sparse_csr_sum_cpu(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor _sparse_csr_sum_cuda(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, ::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/_sparse_mask_projection.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection.h new file mode 100644 index 0000000000000000000000000000000000000000..b247fe7f2ed63d1acc31caf9614844c5d0d43ce6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection.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_mask_projection.out(Tensor self, Tensor mask, bool accumulate_matches=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_mask_projection_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches=false) { + return at::_ops::_sparse_mask_projection_out::call(self, mask, accumulate_matches, out); +} +// aten::_sparse_mask_projection.out(Tensor self, Tensor mask, bool accumulate_matches=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_mask_projection_outf(const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches, at::Tensor & out) { + return at::_ops::_sparse_mask_projection_out::call(self, mask, accumulate_matches, 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_mm_reduce_impl.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl.h new file mode 100644 index 0000000000000000000000000000000000000000..23669a910fe3e0369fa02de0f23490f087f677d2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl.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::_sparse_mm_reduce_impl(Tensor self, Tensor other, str reduce) -> (Tensor, Tensor) +inline ::std::tuple _sparse_mm_reduce_impl(const at::Tensor & self, const at::Tensor & other, c10::string_view reduce) { + return at::_ops::_sparse_mm_reduce_impl::call(self, other, reduce); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0bee9dd3b1fe940398b0740c6e321e5b20f69d5e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_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 _sparse_semi_structured_apply(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_apply_dense.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense.h new file mode 100644 index 0000000000000000000000000000000000000000..b10a1b08b202ab093655d59649848e784d19fda0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense.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::_sparse_semi_structured_apply_dense(Tensor input, Tensor thread_masks) -> Tensor +inline at::Tensor _sparse_semi_structured_apply_dense(const at::Tensor & input, const at::Tensor & thread_masks) { + return at::_ops::_sparse_semi_structured_apply_dense::call(input, thread_masks); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c314edf5a97339002aff5f8c1c6d71cf7d9b41d1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_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 _sparse_semi_structured_apply(const at::Tensor & input, const at::Tensor & thread_masks); +} // 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_semi_structured_tile_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2b42f5f6a9fc9ce49f5a58a86f90e283c4e57984 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_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 _sparse_semi_structured_tile(const at::Tensor & input, c10::string_view algorithm="", bool use_cutlass=true); +} // 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_backward_data_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3730dbc974f33e790f946acddec6a266e611889 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_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_softmax_backward_data_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +TORCH_API at::Tensor & _sparse_softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, 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/_sparse_sum_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sum_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d7b66996bcc6c6880b8ab5a10fe9ea2fa43468c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sum_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 _sparse_sum_backward { + using schema = at::Tensor (const 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_sum_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API _sparse_sum_backward_out { + using schema = at::Tensor & (const 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_sum_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef 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/_stack.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_stack.h new file mode 100644 index 0000000000000000000000000000000000000000..377a3d49ec74ea8cf18d99506f842f3ec5179e92 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_stack.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::_stack(Tensor[] tensors, int dim=0) -> Tensor +inline at::Tensor _stack(at::TensorList tensors, int64_t dim=0) { + return at::_ops::_stack::call(tensors, dim); +} + +// aten::_stack.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _stack_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0) { + return at::_ops::_stack_out::call(tensors, dim, out); +} +// aten::_stack.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _stack_outf(at::TensorList tensors, int64_t dim, at::Tensor & out) { + return at::_ops::_stack_out::call(tensors, 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/_stack_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_stack_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca4c2eaa0635e12f071285f74475f3c5f907959b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_stack_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 _stack(at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & _stack_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & _stack_outf(at::TensorList tensors, 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/_standard_gamma.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma.h new file mode 100644 index 0000000000000000000000000000000000000000..87b285f249dd2f07bec0d8dcfa8b1083acdfff3a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma.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::_standard_gamma(Tensor self, Generator? generator=None) -> Tensor +inline at::Tensor _standard_gamma(const at::Tensor & self, ::std::optional generator=::std::nullopt) { + return at::_ops::_standard_gamma::call(self, generator); +} + +// aten::_standard_gamma.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _standard_gamma_out(at::Tensor & out, const at::Tensor & self, ::std::optional generator=::std::nullopt) { + return at::_ops::_standard_gamma_out::call(self, generator, out); +} +// aten::_standard_gamma.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _standard_gamma_outf(const at::Tensor & self, ::std::optional generator, at::Tensor & out) { + return at::_ops::_standard_gamma_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/_test_autograd_multiple_dispatch_view_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..064fd008fbafd4d5eccc53fb0cc82d66b48942df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_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 _test_autograd_multiple_dispatch_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::_test_autograd_multiple_dispatch_view"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_test_autograd_multiple_dispatch_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/_test_check_tensor_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_check_tensor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4d5353ec5a1865999e6177aa4dd24bb485ede24e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_check_tensor_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 _test_check_tensor(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/_test_check_tensor_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_check_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4ad2219690cbf1049326688cb45ab921bec77f4a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_check_tensor_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 _test_check_tensor { + 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::_test_check_tensor"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_test_check_tensor(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/_test_optional_filled_intlist_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_filled_intlist_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..19cd2327c9a8a709b18af760f05839babb9189c6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_filled_intlist_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_optional_filled_intlist(const at::Tensor & values, at::OptionalIntArrayRef addends); + +} // 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_string_default.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_string_default.h new file mode 100644 index 0000000000000000000000000000000000000000..5e18ac89a579db889fc5a966b88c172fe815b796 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_test_string_default.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::_test_string_default(Tensor dummy, str a="\"'\\", str b='"\'\\') -> Tensor +inline at::Tensor _test_string_default(const at::Tensor & dummy, c10::string_view a="\"'\\", c10::string_view b="\"'\\") { + return at::_ops::_test_string_default::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/_thnn_differentiable_lstm_cell_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_lstm_cell_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..37b93c0958a96acd8b599e9538edff655cb4f52a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_lstm_cell_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::_thnn_differentiable_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor input_gates, Tensor hidden_gates, Tensor? input_bias, Tensor? hidden_bias, Tensor cx, Tensor cy) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _thnn_differentiable_lstm_cell_backward(const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const ::std::optional & input_bias, const ::std::optional & hidden_bias, const at::Tensor & cx, const at::Tensor & cy) { + return at::_ops::_thnn_differentiable_lstm_cell_backward::call(grad_hy, grad_cy, input_gates, hidden_gates, input_bias, hidden_bias, cx, cy); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_lstm_cell_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_lstm_cell_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04da31e20f3fbc33e6d4c821353406287a479f89 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_lstm_cell_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 _thnn_differentiable_lstm_cell_backward(const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const ::std::optional & input_bias, const ::std::optional & hidden_bias, const at::Tensor & cx, const at::Tensor & cy); + +} // 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/_thnn_fused_gru_cell_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..435dfcb51bd35652328870293daa19cc09e7fe2c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_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::_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _thnn_fused_gru_cell_backward(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias) { + return at::_ops::_thnn_fused_gru_cell_backward::call(grad_hy, workspace, has_bias); +} + +// aten::_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!)) +inline ::std::tuple _thnn_fused_gru_cell_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias) { + return at::_ops::_thnn_fused_gru_cell_backward_out::call(grad_hy, workspace, has_bias, out0, out1, out2, out3, out4); +} +// aten::_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!)) +inline ::std::tuple _thnn_fused_gru_cell_backward_outf(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) { + return at::_ops::_thnn_fused_gru_cell_backward_out::call(grad_hy, workspace, has_bias, 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/_thnn_fused_lstm_cell_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1ad3c08fc0b0720d0ef5bc2a7eef26572bd1fe81 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_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::_thnn_fused_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _thnn_fused_lstm_cell_backward(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) { + return at::_ops::_thnn_fused_lstm_cell_backward::call(grad_hy, grad_cy, cx, cy, workspace, has_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/_thnn_fused_lstm_cell_backward_impl_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_impl_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1b420e89e95739ea1158433c7187f8de7c5e098f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_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 ::std::tuple _thnn_fused_lstm_cell_backward_impl(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); + +} // 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/_thnn_fused_lstm_cell_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..92ff524a9ee9e84e24f469cb5ad723e686ada112 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_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 _thnn_fused_lstm_cell_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}); +TORCH_API ::std::tuple _thnn_fused_lstm_cell_outf(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const ::std::optional & input_bias, const ::std::optional & hidden_bias, 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/_to_cpu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_cpu.h new file mode 100644 index 0000000000000000000000000000000000000000..5bb218a4b490259fb151fb08d707c837bcaa671e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_cpu.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::_to_cpu(Tensor[] tensors) -> Tensor[] +inline ::std::vector _to_cpu(at::TensorList tensors) { + return at::_ops::_to_cpu::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/_to_sparse.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse.h new file mode 100644 index 0000000000000000000000000000000000000000..68405be0c30212fd102b0db97ddd1a0170cad0ae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse.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::_to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_out(at::Tensor & out, const at::Tensor & self, int64_t sparse_dim) { + return at::_ops::_to_sparse_sparse_dim_out::call(self, sparse_dim, out); +} +// aten::_to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_outf(const at::Tensor & self, int64_t sparse_dim, at::Tensor & out) { + return at::_ops::_to_sparse_sparse_dim_out::call(self, sparse_dim, out); +} + +// aten::_to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_out(at::Tensor & out, const at::Tensor & self, ::std::optional layout=::std::nullopt, at::OptionalIntArrayRef blocksize=::std::nullopt, ::std::optional dense_dim=::std::nullopt) { + return at::_ops::_to_sparse_out::call(self, layout, blocksize, dense_dim, out); +} +// aten::_to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_outf(const at::Tensor & self, ::std::optional layout, at::OptionalIntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out) { + return at::_ops::_to_sparse_out::call(self, layout, 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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f10b1c32e9748b7c41adb8b852fed6632291f327 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_bsr_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 & _to_sparse_bsr_out(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out); +TORCH_API at::Tensor dense_to_sparse_bsr(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor coo_to_sparse_bsr(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor sparse_compressed_to_sparse_bsr(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::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_sparse_csc_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..05c7b7cb2301115c581d560831b93c612b23d10b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csc_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_csc { + 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_sparse_csc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dense_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dense_dim); +}; + +struct TORCH_API _to_sparse_csc_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_sparse_csc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_to_sparse_csc.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional dense_dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dense_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/_to_sparse_csr_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csr_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6ab386bbb26d6ba61a63641ce8c360d99f551ef4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csr_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_csr(const at::Tensor & self, ::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/_trilinear_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a5cd721014f9bb4af0172822a7e78c5d6bfa361 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_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 _trilinear(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); + +} // 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/_unique2_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unique2_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1cfbc002872cedde251b370f9b5706df0a795cea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unique2_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 _unique2(const at::Tensor & self, bool sorted=true, bool return_inverse=false, bool return_counts=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/_unsafe_index_put.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_put.h new file mode 100644 index 0000000000000000000000000000000000000000..74c6924754eb54db7290093a95e05cb2d5f96d59 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_put.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_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor +inline at::Tensor _unsafe_index_put(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false) { + return at::_ops::_unsafe_index_put::call(self, indices, values, accumulate); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_view_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b21e96c803d16031651cfea27c2a64c3bbee1b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_view_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 _unsafe_view(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor _unsafe_view_symint(const at::Tensor & self, c10::SymIntArrayRef size); +TORCH_API at::Tensor & _unsafe_view_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor & _unsafe_view_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & _unsafe_view_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size); +TORCH_API at::Tensor & _unsafe_view_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, 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/_upsample_bicubic2d_aa_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..3644dc85502ed72bb6dd4172fe910a411f11191d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_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_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + 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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + 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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & _upsample_bicubic2d_aa_backward_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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & _upsample_bicubic2d_aa_backward_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) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); +} +namespace symint { + template >> + 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) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); + } +} + +// aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor _upsample_bicubic2d_aa_backward(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) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, output_size, input_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_nearest_exact1d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bde9f65d14eb2cad39c68a3cf9864f667e3d601 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_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_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); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_out(at::Tensor & grad_input, 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_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::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_nearest_exact1d_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e417f849c109aafcca7ea398f4159766c302ef23 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_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(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); + +} // 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_exact3d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6dc7c439c67010d92ef471ad7a4c82f263b87f6b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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_exact3d_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); +TORCH_API at::Tensor _upsample_nearest_exact3d_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); + +} // 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_exact3d_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8b04699c152af6f0835bb7d1d0c8d5c4cc39ec38 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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__upsample_nearest_exact3d_backward_out_cpu : public at::meta::structured__upsample_nearest_exact3d_backward { +void impl(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, const at::Tensor & grad_input); +}; +struct TORCH_API structured__upsample_nearest_exact3d_backward_out_cuda : public at::meta::structured__upsample_nearest_exact3d_backward { +void impl(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, 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/_upsample_nearest_exact3d_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bc8fae32797bb35ab75c04b70bb6ce8c0467f491 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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 _upsample_nearest_exact3d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, 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_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "_upsample_nearest_exact3d_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!)"; + static at::Tensor & call(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); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _upsample_nearest_exact3d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, 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_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_upsample_nearest_exact3d_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"; + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +}} // 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_rnn_flatten_weight.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..7c23de43bde97961add1341e06c0bc0ba4bb759a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_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::_use_cudnn_rnn_flatten_weight() -> bool +inline bool _use_cudnn_rnn_flatten_weight() { + return at::_ops::_use_cudnn_rnn_flatten_weight::call(); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..14f4ce9fb8e8f534a28aa7c9cf08e398d0aa5b7b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_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 _use_cudnn_rnn_flatten_weight(); + +} // 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/_use_cudnn_rnn_flatten_weight_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8e83acb04496cf331cc4a61e2ac7397b0f083d6a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_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 _use_cudnn_rnn_flatten_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/_validate_sparse_bsr_tensor_args_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsr_tensor_args_native.h new file mode 100644 index 0000000000000000000000000000000000000000..77832ee04f3bae172aa53dd88bf6d1df80f16973 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_bsr_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_bsr_tensor_args(const at::Tensor & crow_indices, const at::Tensor & col_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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b1b401eaa401496a3b5741fe8bcd208ece2d4a80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_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_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); +} // 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/_values_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_values_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..e5a64c92f04c554478d6b3ecbbbf1fd8136a0839 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_values_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::_values_copy(Tensor self) -> Tensor +inline at::Tensor _values_copy(const at::Tensor & self) { + return at::_ops::_values_copy::call(self); +} + +// aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _values_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_values_copy_out::call(self, out); +} +// aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _values_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_values_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/_weight_int4pack_mm_for_cpu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_for_cpu.h new file mode 100644 index 0000000000000000000000000000000000000000..5e4ebcd754f13b27e3a0b69ba11fd8b92487c7a1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_for_cpu.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_int4pack_mm_for_cpu(Tensor self, Tensor mat2, int qGroupSize, Tensor qScaleAndZeros) -> Tensor +inline at::Tensor _weight_int4pack_mm_for_cpu(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros) { + return at::_ops::_weight_int4pack_mm_for_cpu::call(self, mat2, qGroupSize, qScaleAndZeros); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..22aec02effd79696d3a740cbc40025257fcea4c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface_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::_weight_norm_interface_backward(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim) -> (Tensor, Tensor) +inline ::std::tuple _weight_norm_interface_backward(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim) { + return at::_ops::_weight_norm_interface_backward::call(grad_w, saved_v, saved_g, saved_norms, dim); +} + +// aten::_weight_norm_interface_backward.out(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _weight_norm_interface_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim) { + return at::_ops::_weight_norm_interface_backward_out::call(grad_w, saved_v, saved_g, saved_norms, dim, out0, out1); +} +// aten::_weight_norm_interface_backward.out(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _weight_norm_interface_backward_outf(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_weight_norm_interface_backward_out::call(grad_w, saved_v, saved_g, saved_norms, 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/_weight_norm_interface_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..939c7c0c5127f471da87b4e1c1d3f2ecd08ce295 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_norm_interface_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 _weight_norm_interface(const at::Tensor & v, const at::Tensor & g, int64_t dim=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/absolute_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/absolute_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c6455b0b912e9569c873180cfb8c07530c4fafec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/absolute_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 absolute(const at::Tensor & self); +TORCH_API at::Tensor & absolute_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & absolute_(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/acos.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos.h new file mode 100644 index 0000000000000000000000000000000000000000..27248eb25fe77035e20f53bce5381432da8f9b38 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos.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::acos(Tensor self) -> Tensor +inline at::Tensor acos(const at::Tensor & self) { + return at::_ops::acos::call(self); +} + +// aten::acos_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & acos_(at::Tensor & self) { + return at::_ops::acos_::call(self); +} + +// aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & acos_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::acos_out::call(self, out); +} +// aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & acos_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::acos_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/acos_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..4f9271ef2cb04ce52c43d35ef511d92f0552ce46 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/acos_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_acos : 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/adaptive_avg_pool2d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cb027a606ed935d7b96fbbfe76097ddeee93dd7a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_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_avg_pool2d_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::adaptive_avg_pool2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "adaptive_avg_pool2d.out(Tensor self, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out); +}; + +struct TORCH_API adaptive_avg_pool2d { + 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::adaptive_avg_pool2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "adaptive_avg_pool2d(Tensor self, SymInt[2] output_size) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef 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_avg_pool3d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3201162b6c73637bd276305777c414b24012d97 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_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 & adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor & adaptive_avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor & adaptive_avg_pool3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size); +TORCH_API at::Tensor & adaptive_avg_pool3d_symint_outf(const at::Tensor & self, 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/adaptive_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f83c1ff37128ad1931e3f5c40da7d68b36f9c603 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_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 adaptive_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); + +} // 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/adaptive_max_pool2d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..11e1ae5cd8f575ac2d6cbdcf0a52b75702c9ff84 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_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_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool2d_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_pool2d_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_pool2d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e9e3adcd6f737c7cec0d6dd4ff66d63282f4c984 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_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_adaptive_max_pool2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self, const 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/adaptive_max_pool2d_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5beb2f90e3814017fc38f8e1786e881dff6f0009 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_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 adaptive_max_pool2d(const at::Tensor & self, at::IntArrayRef output_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/adaptive_max_pool3d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..463e249fd3118bfc88622e37f6b2d009ffd04d1a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_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 adaptive_max_pool3d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool3d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, 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/adaptive_max_pool3d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..c21b4d5fb5a367536ab7f26096911c4a9f42f9fd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_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_pool3d : 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_pool3d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d0e923b446d50ab83c0c939f4cae0de83f9c93c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_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_pool3d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool3d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool3d_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/add_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/add_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8a244bf1c016bb3a4d069e182236359ae766a2a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/add_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 add_Tensor { + using schema = 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::add"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API add__Tensor { + using schema = at::Tensor & (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::add_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API add_out { + using schema = 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::add"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +}; + +struct TORCH_API add_Scalar { + 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::add"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "add.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API add__Scalar { + 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::add_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "add_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API add_Scalar_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::add"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "add.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, 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/addcmul_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c606de0e9e312b983babf7bb66259770e14159ba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_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 addcmul(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcmul_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); + +} // 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/addcmul_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..45cae7b293413357ab9b5d7d10dcc7b684928253 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_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 addcmul(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcmul_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & addcmul_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=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/addmm_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba35946c04cb08b23afa6425adf5186ec63d95ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_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 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 & addmm_(at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); + +} // 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/addmm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4a66257846f75aeb0244fffda26779903ec99694 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_cuda_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 cuda { + +TORCH_API at::Tensor 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 & 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); +TORCH_API at::Tensor & 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); +TORCH_API at::Tensor & addmm_(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 addmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, at::ScalarType out_dtype, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, at::ScalarType out_dtype, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, at::ScalarType out_dtype, const at::Scalar & beta, const at::Scalar & alpha, 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/addmv_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..25d3fc69cc8960e0e95413698ce4c2e6fa227aba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/addmv_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_addmv_out_cpu : public at::meta::structured_addmv { +void impl(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, const at::Tensor & out); +}; +struct TORCH_API structured_addmv_out_cuda : public at::meta::structured_addmv { +void impl(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, const at::Tensor & out); +}; +TORCH_API at::Tensor & addmv_out_sparse_compressed(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & addmv_out_sparse_compressed_cuda(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, 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/adjoint_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adjoint_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bc2ac0f87c837d2c6ccc9d0846f1b8ffe3354010 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/adjoint_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 adjoint { + 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::adjoint"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "adjoint(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/affine_grid_generator_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/affine_grid_generator_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3ab10f19a8e79bc43837fdb38f67a59556d3811a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/affine_grid_generator_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 affine_grid_generator { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::affine_grid_generator"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "affine_grid_generator(Tensor theta, SymInt[] size, bool align_corners) -> Tensor"; + static at::Tensor call(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners); +}; + +struct TORCH_API affine_grid_generator_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::affine_grid_generator"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "affine_grid_generator.out(Tensor theta, SymInt[] size, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners, 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/alias_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alias_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d2cb9d2b6c70240f87c445280f267b1f151839c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alias_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 & alias_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor alias_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/align_tensors_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_tensors_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9b8bbe99a80da8c0e85e5db1a834e8a5a200e3bd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_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 align_tensors(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/align_to_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_to_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8328192c20150576121117e7b441da3fc2299101 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_to_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 align_to(const at::Tensor & self, at::DimnameList names); +TORCH_API at::Tensor align_to(const at::Tensor & self, at::DimnameList order, int64_t ellipsis_idx); +} // 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/align_to_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_to_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a3c0c7820c47abc31b80447d4838fd65b8647197 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/align_to_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 align_to { + using schema = at::Tensor (const at::Tensor &, at::DimnameList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::align_to"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "align_to(Tensor(a) self, Dimname[] names) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::DimnameList names); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList names); +}; + +struct TORCH_API align_to_ellipsis_idx { + using schema = at::Tensor (const at::Tensor &, at::DimnameList, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::align_to"; + static constexpr const char* overload_name = "ellipsis_idx"; + static constexpr const char* schema_str = "align_to.ellipsis_idx(Tensor(a) self, Dimname[] order, int ellipsis_idx) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::DimnameList order, int64_t ellipsis_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList order, int64_t ellipsis_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/all_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/all_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d0d0eea40fd9e128aa4ceb88c9212052e20957f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/all_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 all(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor all(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor all(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/all_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/all_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a17496aac2a40cbe8b9745f6cc0642c5ade8deee --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/all_cuda_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 cuda { + +TORCH_API at::Tensor all(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor & all_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor all(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & all_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor all(const at::Tensor & self); +TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & all_outf(const at::Tensor & self, 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/alpha_dropout_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alpha_dropout_native.h new file mode 100644 index 0000000000000000000000000000000000000000..328ce9be552dd9ce1cfd288bc745e90c45c427c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/alpha_dropout_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 alpha_dropout(const at::Tensor & input, double p, bool train); +TORCH_API at::Tensor & alpha_dropout_(at::Tensor & self, double p, bool train); +} // 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/amax_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..864129724fe0034026073e0a57c301f6166bd163 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/amax_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_amax_out : public at::meta::structured_amax { +void impl(const at::Tensor & self, at::IntArrayRef 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/aminmax_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b1c178711eca72a37930b58ba1da928cbfc9f0da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_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 aminmax(const at::Tensor & self, ::std::optional dim=::std::nullopt, 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/angle_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/angle_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..81e457b1adedfa7b9d5b80f86ca26362d251934c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/angle_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 angle(const at::Tensor & self); +TORCH_API at::Tensor & angle_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & angle_outf(const at::Tensor & self, 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/any_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e3cbc9d17916489ad7c1fdd6c6a1a68dadd29fb2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_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 any(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor any(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor any(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/any_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5589e7f0283d2cc3fdae4c3f992cfb6ccfda3e12 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_meta_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 meta { + +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 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/any_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_native.h new file mode 100644 index 0000000000000000000000000000000000000000..77f8d3ffe49ce7d9661958c71e4456d1936f2d9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/any_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 +#include + +namespace at { +namespace native { +struct TORCH_API structured_any_out : public at::meta::structured_any_dim { +void impl(const at::Tensor & self, int64_t dim, bool keepdim, const at::Tensor & out); +}; +TORCH_API at::Tensor any_dims_default(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & any_dims_out_default(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); +struct TORCH_API structured_any_dims_out : public at::meta::structured_any_dims { +void impl(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, const at::Tensor & out); +}; +TORCH_API at::Tensor any(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); +struct TORCH_API structured_any_all_out : public at::meta::structured_any { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor any_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/arange_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e13dc99604c79d42b9caf0218c446666e834294 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arange_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor arange(const at::Scalar & end, at::TensorOptions options={}); +TORCH_API at::Tensor arange(const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & arange_out(at::Tensor & out, const at::Scalar & end); +TORCH_API at::Tensor & arange_outf(const at::Scalar & end, at::Tensor & out); +TORCH_API at::Tensor arange(const at::Scalar & start, const at::Scalar & end, at::TensorOptions options={}); +TORCH_API at::Tensor arange(const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor arange(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::TensorOptions options={}); +TORCH_API at::Tensor arange(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); + +} // 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/arccos_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arccos_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9f35ded4a53270e5613496b9856f4ebd33224c05 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arccos_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 arccos(const at::Tensor & self); +TORCH_API at::Tensor & arccos_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & arccos_(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/arccosh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arccosh.h new file mode 100644 index 0000000000000000000000000000000000000000..4c303ef5e1909b212d5ec4e0a94046a4cf4dabfa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arccosh.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::arccosh(Tensor self) -> Tensor +inline at::Tensor arccosh(const at::Tensor & self) { + return at::_ops::arccosh::call(self); +} + +// aten::arccosh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & arccosh_(at::Tensor & self) { + return at::_ops::arccosh_::call(self); +} + +// aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arccosh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::arccosh_out::call(self, out); +} +// aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arccosh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::arccosh_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/arcsin_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arcsin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..747a8559b9a10c739a4484b529ef52bbbbc6a701 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arcsin_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 arcsin(const at::Tensor & self); +TORCH_API at::Tensor & arcsin_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & arcsin_(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/arctan2_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arctan2_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b532ecedc8fa350b62207e319602df9742a78244 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/arctan2_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 arctan2(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & arctan2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & arctan2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & arctan2_(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/argmax_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..73e3089266b5a99cfe22dccace84ba4ab50c1375 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argmax_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 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 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/argwhere_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argwhere_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5e1842244686ddcd1a0a701c5128cf64a15292b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/argwhere_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 argwhere(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/as_strided_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8bd63b91c809589e30ee5bf42ca088dabd014a82 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_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 { + 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"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a)"; + 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_ { + using schema = const 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_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset); +}; + +}} // 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/asin_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/asin_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9afcaa70ffbd8a5da9a2ed3f3aee15c08a07dc68 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/asin_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 asin(const at::Tensor & self); +TORCH_API at::Tensor & asin_(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/asin_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/asin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9ee00f0e254f092a23a12bfcf78cfceb841c8b94 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/asin_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_asin_out : public at::meta::structured_asin { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor asin_sparse(const at::Tensor & self); +TORCH_API at::Tensor & asin_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & asin_sparse_(at::Tensor & self); +TORCH_API at::Tensor asin_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & asin_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & asin_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/asin_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/asin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a4f3e53669f76b62312a9db50fc1bd4573753af2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/asin_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 asin { + 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::asin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "asin(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 asin_ { + 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::asin_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "asin_(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 asin_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::asin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "asin.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/atanh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh.h new file mode 100644 index 0000000000000000000000000000000000000000..22d8eb88f39b944797205889d02b75c986ee3ae4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh.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::atanh(Tensor self) -> Tensor +inline at::Tensor atanh(const at::Tensor & self) { + return at::_ops::atanh::call(self); +} + +// aten::atanh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & atanh_(at::Tensor & self) { + return at::_ops::atanh_::call(self); +} + +// aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::atanh_out::call(self, out); +} +// aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::atanh_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/atanh_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd2086f376e42e95c69f6d541e6ac57a0bb5f52a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_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 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 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/atanh_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..675e8e3eff1f9654f8d4df150921fb05cdd4fb98 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/atanh_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_atanh_out : public at::meta::structured_atanh { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor atanh_sparse(const at::Tensor & self); +TORCH_API at::Tensor & atanh_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atanh_sparse_(at::Tensor & self); +TORCH_API at::Tensor atanh_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & atanh_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atanh_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/avg_pool2d_backward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39bacbef26829b894f0c5d95ee08ede5abd5fc7b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_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_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 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_pool2d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..05f2c349048c816f3ab8c763eae1f774fdb6ea78 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_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 avg_pool2d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::avg_pool2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "avg_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, 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, ::std::optional divisor_override, 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, ::std::optional divisor_override, at::Tensor & out); +}; + +struct TORCH_API avg_pool2d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::avg_pool2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "avg_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> 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, ::std::optional divisor_override); + 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, ::std::optional divisor_override); +}; + +}} // 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_pool3d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..4b1fb1e439bac26ae088922db4036853217bffa6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_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_pool3d : public at::impl::MetaBase { + + + void meta(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/baddbmm_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39f49e394d60bdd76676812642f21fd5a5b51c9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_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 baddbmm(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & baddbmm_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); + +} // 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/batch_norm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..97f989e8a172725742022c42e302b4a16e4b012a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_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::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor +inline at::Tensor 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, bool cudnn_enabled) { + return at::_ops::batch_norm::call(input, weight, bias, running_mean, running_var, training, momentum, eps, cudnn_enabled); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a0bb76d11aeac3a2968cf1be7b5064591a6d2836 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_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_backward_reduce_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, 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); +TORCH_API ::std::tuple batch_norm_backward_reduce_outf(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); + +} // 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_backward_reduce_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e7455617099dc10b2d22363cdfa6fe6705543c85 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_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 batch_norm_backward_reduce { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm_backward_reduce"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "batch_norm_backward_reduce(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, bool input_g, bool weight_g, bool bias_g) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API batch_norm_backward_reduce_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, bool, bool, bool, 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::batch_norm_backward_reduce"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "batch_norm_backward_reduce.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, bool input_g, bool weight_g, bool bias_g, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +}} // 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_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fe1a4a91360bd2ec5ea65fa16c99bc19148e62fd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_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 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, bool cudnn_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/batch_norm_gather_stats_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..caa4e8e496e3884f1bb19ac0b5e28ad3b6facbe3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_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_gather_stats(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); + +} // 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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d3ca432241247668208d1664db4e66a48711dc4d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_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 { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor"; + static at::Tensor call(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, bool cudnn_enabled); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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, bool cudnn_enabled); +}; + +}} // 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/bernoulli_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fc75ee3657e5d09465bff0f3602b67689fd986c6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bernoulli_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 & 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 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/binary_cross_entropy_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8b6844c567af4996903eeb73e44513910b4d85e9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_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 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 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/binary_cross_entropy_with_logits_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_with_logits_native.h new file mode 100644 index 0000000000000000000000000000000000000000..073f88d687b9c8716ab66fad77bd8e2a253bc912 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_with_logits_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 binary_cross_entropy_with_logits(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, const ::std::optional & pos_weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & binary_cross_entropy_with_logits_out(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, const ::std::optional & pos_weight, int64_t reduction, 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/bincount_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ba958c85ed7be6d4a8e0896f6c96127c002ec15 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bincount_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 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 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/binomial_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binomial_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6acff0955f45b13356934ed9aed50a3010bf57c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/binomial_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 & binomial_out(at::Tensor & out, const at::Tensor & count, const at::Tensor & prob, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & binomial_outf(const at::Tensor & count, const at::Tensor & prob, ::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/bitwise_and_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_and_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ea680684f3e6dca9dd4bbbcc58ed81f54289b0b1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_and_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 bitwise_and(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_and_(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/bitwise_and_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_and_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..69debd6c535724142873b67f44dedb8e930db108 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_and_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 bitwise_and(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_and_(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/bitwise_and_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_and_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8d49f3e5f074a0da25e766b21d05a2f14278edb9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_and_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 bitwise_and_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::bitwise_and"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "bitwise_and.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 bitwise_and_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::bitwise_and"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "bitwise_and.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 bitwise_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::bitwise_and"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "bitwise_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 bitwise_and_Scalar_Tensor { + 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::bitwise_and"; + static constexpr const char* overload_name = "Scalar_Tensor"; + static constexpr const char* schema_str = "bitwise_and.Scalar_Tensor(Scalar self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API bitwise_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::bitwise_and"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bitwise_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 bitwise_and__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::bitwise_and_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "bitwise_and_.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 bitwise_and__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::bitwise_and_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bitwise_and_.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 bitwise_and_Scalar_Tensor_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::bitwise_and"; + static constexpr const char* overload_name = "Scalar_Tensor_out"; + static constexpr const char* schema_str = "bitwise_and.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & 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/bitwise_or_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..429a1d4fe0d37e3d1d7726ca1c78d5b918af87a5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_or_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 bitwise_or(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_(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/bitwise_right_shift_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5b9bdf6f24ab41c2667107bba20c06865a721f2b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_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_right_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_right_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_right_shift_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2b5785554c6c9771266182077ed01a85fe96d65b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_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_right_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_right_shift_(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_right_shift_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..74b5793d5a4159fab7591aca4055e98c3e52c2c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_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 bitwise_right_shift_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::bitwise_right_shift"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bitwise_right_shift.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 bitwise_right_shift__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::bitwise_right_shift_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bitwise_right_shift_.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 bitwise_right_shift_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::bitwise_right_shift"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "bitwise_right_shift.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 bitwise_right_shift_Tensor_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::bitwise_right_shift"; + static constexpr const char* overload_name = "Tensor_Scalar"; + static constexpr const char* schema_str = "bitwise_right_shift.Tensor_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 bitwise_right_shift__Tensor_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::bitwise_right_shift_"; + static constexpr const char* overload_name = "Tensor_Scalar"; + static constexpr const char* schema_str = "bitwise_right_shift_.Tensor_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 bitwise_right_shift_Tensor_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::bitwise_right_shift"; + static constexpr const char* overload_name = "Tensor_Scalar_out"; + static constexpr const char* schema_str = "bitwise_right_shift.Tensor_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 bitwise_right_shift_Scalar_Tensor { + 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::bitwise_right_shift"; + static constexpr const char* overload_name = "Scalar_Tensor"; + static constexpr const char* schema_str = "bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API bitwise_right_shift_Scalar_Tensor_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::bitwise_right_shift"; + static constexpr const char* overload_name = "Scalar_Tensor_out"; + static constexpr const char* schema_str = "bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & 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/blackman_window_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_window_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b68e852ad30b5554104a14ddb386d0a27f68027a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_window_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 blackman_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::blackman_window"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "blackman_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 blackman_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::blackman_window"; + static constexpr const char* overload_name = "periodic"; + static constexpr const char* schema_str = "blackman_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 blackman_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::blackman_window"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "blackman_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 blackman_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::blackman_window"; + static constexpr const char* overload_name = "periodic_out"; + static constexpr const char* schema_str = "blackman_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); +}; + +}} // 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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..133c30b922d63ce644a46327a229201d8756acd7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_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 +#include + +namespace at { +namespace native { +struct TORCH_API structured_bmm_out_cpu : public at::meta::structured_bmm { +void impl(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & out); +}; +struct TORCH_API structured_bmm_out_cuda : public at::meta::structured_bmm { +void impl(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & out); +}; +TORCH_API at::Tensor bmm_nested(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor bmm_nested_cuda(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor bmm_sparse_cpu(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_out_sparse_cpu(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor bmm_sparse_cuda(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_out_sparse_cuda(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor & bmm_out_sparse_csr_cuda(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _bmm_dtype_cuda(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & _bmm_out_dtype_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/broadcast_tensors.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_tensors.h new file mode 100644 index 0000000000000000000000000000000000000000..ff8f065b94020b2d47c5032a00ce6a2edf87d7f9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_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::broadcast_tensors(Tensor[] tensors) -> Tensor[] +inline ::std::vector broadcast_tensors(at::TensorList tensors) { + return at::_ops::broadcast_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/can_cast.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/can_cast.h new file mode 100644 index 0000000000000000000000000000000000000000..c97f59cf88ef685759788ebe02c355ee11255a6d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/can_cast.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::can_cast(ScalarType from_, ScalarType to) -> bool +inline bool can_cast(at::ScalarType from_, at::ScalarType to) { + return at::_ops::can_cast::call(from_, to); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod.h new file mode 100644 index 0000000000000000000000000000000000000000..3cfe82679709874c8819c37fdb66718d6405d1c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod.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::cartesian_prod(Tensor[] tensors) -> Tensor +inline at::Tensor cartesian_prod(at::TensorList tensors) { + return at::_ops::cartesian_prod::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/cartesian_prod_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..87e101253892f20477cc7b79b3a96823f738f1d7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cartesian_prod_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 cartesian_prod { + 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::cartesian_prod"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cartesian_prod(Tensor[] tensors) -> Tensor"; + static at::Tensor call(at::TensorList tensors); + static at::Tensor 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/cauchy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy.h new file mode 100644 index 0000000000000000000000000000000000000000..b7b7cc29c052af947648b2c56a84cc33089b82a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy.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::cauchy.out(Tensor self, float median=0, float sigma=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cauchy_out(at::Tensor & out, const at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt) { + return at::_ops::cauchy_out::call(self, median, sigma, generator, out); +} +// aten::cauchy.out(Tensor self, float median=0, float sigma=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cauchy_outf(const at::Tensor & self, double median, double sigma, ::std::optional generator, at::Tensor & out) { + return at::_ops::cauchy_out::call(self, median, sigma, generator, out); +} + +// aten::cauchy(Tensor self, float median=0, float sigma=1, *, Generator? generator=None) -> Tensor +inline at::Tensor cauchy(const at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt) { + return at::_ops::cauchy::call(self, median, sigma, generator); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a7023fe4fa5730ea6bd7310a3655c29f36ab0cf7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_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 cauchy(const at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & cauchy_out(at::Tensor & out, const at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & cauchy_outf(const at::Tensor & self, double median, double sigma, ::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/ccol_indices_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..84716b3ced498be5f222cae8aea5f54d2dfe0b67 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_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 ccol_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/channel_shuffle_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7608b6470a58154863a21a37deddbc0c9fc9a478 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle_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 & channel_shuffle_out_symint(const at::Tensor & self, c10::SymInt groups, at::Tensor & out); +TORCH_API at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor channel_shuffle_quantized_cpu(const at::Tensor & self, 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/cholesky_inverse_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_inverse_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f35d36e2aeec3c96a76b9f3645e657891ee81db6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_inverse_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 cholesky_inverse(const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & cholesky_inverse_out(at::Tensor & out, const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & cholesky_inverse_outf(const at::Tensor & self, bool upper, 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/cholesky_solve_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_solve_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e73ccd0b3bdd5976030b95a4de0d3e41932d80f0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_solve_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 cholesky_solve(const at::Tensor & self, const at::Tensor & input2, bool upper=false); +TORCH_API at::Tensor & cholesky_solve_out(const at::Tensor & self, const at::Tensor & input2, bool upper, 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/chunk.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/chunk.h new file mode 100644 index 0000000000000000000000000000000000000000..667e3e487a02d011d3b6b7b7b180bdacd4bf715f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/chunk.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::chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[] +inline ::std::vector chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0) { + return at::_ops::chunk::call(self, chunks, 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/clamp_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf1ac5d47957a4b97d8d5988b2dfb04cc7b66415 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_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 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 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/clip.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clip.h new file mode 100644 index 0000000000000000000000000000000000000000..9ec34f313d94d57317045173e3b9dfed256f58a5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/clip.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::clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor +inline at::Tensor clip(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max=::std::nullopt) { + return at::_ops::clip::call(self, min, max); +} + +// aten::clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor +inline at::Tensor clip(const at::Tensor & self, const ::std::optional & min={}, const ::std::optional & max={}) { + return at::_ops::clip_Tensor::call(self, min, max); +} + +// aten::clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) +inline at::Tensor & clip_(at::Tensor & self, const ::std::optional & min, const ::std::optional & max=::std::nullopt) { + return at::_ops::clip_::call(self, min, max); +} + +// aten::clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) +inline at::Tensor & clip_(at::Tensor & self, const ::std::optional & min={}, const ::std::optional & max={}) { + return at::_ops::clip__Tensor::call(self, min, max); +} + +// aten::clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clip_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max=::std::nullopt) { + return at::_ops::clip_out::call(self, min, max, out); +} +// aten::clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clip_outf(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out) { + return at::_ops::clip_out::call(self, min, max, out); +} + +// aten::clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clip_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & min={}, const ::std::optional & max={}) { + return at::_ops::clip_Tensor_out::call(self, min, max, out); +} +// aten::clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clip_outf(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out) { + return at::_ops::clip_Tensor_out::call(self, min, 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/coalesce_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/coalesce_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..034555ca31208f3adc8f48b8c356f2494efbe8cf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/coalesce_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 coalesce { + 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::coalesce"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "coalesce(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/col2im_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col2im_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0ad5ca942bee382e9af06227739c792c2793113e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col2im_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 col2im(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor col2im_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_outf(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor & col2im_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, 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/col_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b3a69fedd74e05e99cbdb0d31f6a83a7c253f70 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_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 col_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/col_indices_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c121793c597d9f2fb72d5745445d0903d605199e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/col_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 col_indices_default(const at::Tensor & self); +TORCH_API at::Tensor col_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/combinations.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/combinations.h new file mode 100644 index 0000000000000000000000000000000000000000..5f0c58214a7e4995f3cae4f54c5cc0dc26000c80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/combinations.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::combinations(Tensor self, int r=2, bool with_replacement=False) -> Tensor +inline at::Tensor combinations(const at::Tensor & self, int64_t r=2, bool with_replacement=false) { + return at::_ops::combinations::call(self, r, with_replacement); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4730c69f853ee887d2877072b04e34063f82dfba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/complex_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 complex(const at::Tensor & real, const at::Tensor & imag); +TORCH_API at::Tensor & complex_out(const at::Tensor & real, const at::Tensor & imag, 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/constant_pad_nd.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd.h new file mode 100644 index 0000000000000000000000000000000000000000..78c71dba347f25a47989a320e454b5908db689c3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd.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::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor +inline at::Tensor constant_pad_nd(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd::call(self, c10::fromIntArrayRefSlow(pad), value); +} +namespace symint { + template >> + at::Tensor constant_pad_nd(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd::call(self, c10::fromIntArrayRefSlow(pad), value); + } +} + +// aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor +inline at::Tensor constant_pad_nd_symint(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd::call(self, pad, value); +} +namespace symint { + template >> + at::Tensor constant_pad_nd(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd::call(self, pad, value); + } +} + +// aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & constant_pad_nd_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd_out::call(self, c10::fromIntArrayRefSlow(pad), value, out); +} +namespace symint { + template >> + at::Tensor & constant_pad_nd_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd_out::call(self, c10::fromIntArrayRefSlow(pad), value, out); + } +} + +// aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & constant_pad_nd_outf(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value, at::Tensor & out) { + return at::_ops::constant_pad_nd_out::call(self, c10::fromIntArrayRefSlow(pad), value, out); +} +namespace symint { + template >> + at::Tensor & constant_pad_nd_outf(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value, at::Tensor & out) { + return at::_ops::constant_pad_nd_out::call(self, c10::fromIntArrayRefSlow(pad), value, out); + } +} + +// aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & constant_pad_nd_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd_out::call(self, pad, value, out); +} +namespace symint { + template >> + at::Tensor & constant_pad_nd_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value=0) { + return at::_ops::constant_pad_nd_out::call(self, pad, value, out); + } +} + +// aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & constant_pad_nd_symint_outf(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, at::Tensor & out) { + return at::_ops::constant_pad_nd_out::call(self, pad, value, out); +} +namespace symint { + template >> + at::Tensor & constant_pad_nd_outf(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, at::Tensor & out) { + return at::_ops::constant_pad_nd_out::call(self, pad, value, 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/constant_pad_nd_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5d157e214810c414fecf09265a055f41580deb5b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd_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 constant_pad_nd(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0); +TORCH_API at::Tensor & constant_pad_nd_out_symint(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, 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/contiguous_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34f0f5a748cdbcb99091ec6e42595edd298dcba9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/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 at::Tensor 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/contiguous_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ca21276fb318b1e70644ecfb5aaf1e06261cae1e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous_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 contiguous { + using schema = at::Tensor (const at::Tensor &, at::MemoryFormat); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::contiguous"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::MemoryFormat memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::MemoryFormat memory_format); +}; + +}} // 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/conv2d_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..74d6931dc242ceb0dfc6dd0d9a8de3c733f0ea03 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv2d_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 conv2d(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); +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(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); +TORCH_API at::Tensor conv2d_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); + +} // 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/conv3d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a81e07e53abc75175d1b337d9d634648a829cf46 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv3d_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 conv3d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, 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::conv3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conv3d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, SymInt groups=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 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::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API conv3d_padding { + 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::conv3d"; + static constexpr const char* overload_name = "padding"; + static constexpr const char* schema_str = "conv3d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, str padding=\"valid\", SymInt[3] dilation=1, SymInt groups=1) -> 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/conv_tbc_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..2fd29c2cab90920a823eb0625d74e4dff47945ec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_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::conv_tbc_backward(Tensor self, Tensor input, Tensor weight, Tensor bias, int pad) -> (Tensor, Tensor, Tensor) +inline ::std::tuple conv_tbc_backward(const at::Tensor & self, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & bias, int64_t pad) { + return at::_ops::conv_tbc_backward::call(self, input, weight, bias, pad); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7a7f0cebbf874565b3b8ecf6ce7852761752bc7d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_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 conv_tbc(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad=0); +TORCH_API at::Tensor & conv_tbc_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad=0); +TORCH_API at::Tensor & conv_tbc_outf(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad, 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/conv_transpose2d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cb8138078eaee8ca810b150875233d7b6d16820f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose2d_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 conv_transpose2d_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 output_padding=c10::SymInt(0), c10::SymInt groups=1, c10::SymIntArrayRef dilation=c10::SymInt(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/convolution_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f071c35a88475dffbe1224d73147a8ad2282eb50 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_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 ::std::tuple convolution_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalIntArrayRef bias_sizes, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_symint(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); + +} // 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/convolution_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5bb9354f3921d2629b7381de506ba773af236818 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_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 convolution_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::OptionalSymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::convolution_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +}; + +struct TORCH_API convolution_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::OptionalSymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, ::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::convolution_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, 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_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::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/convolution_backward_overrideable_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_overrideable_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6a6845b876c99a64eb36f4644ac46519188d2e3a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_overrideable_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 convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_overrideable_out_symint(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +} // 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/copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c08c422ed4c57f518c36176bf9336d71a1d94f3a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/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 copy(const at::Tensor & self, const at::Tensor & src, bool non_blocking=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/copy_sparse_to_sparse_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fbe36f7856520384f9b801349e34ad14407622e1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_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 copy_sparse_to_sparse_ { + using schema = at::Tensor & (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::copy_sparse_to_sparse_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & src, bool non_blocking); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & src, bool non_blocking); +}; + +struct TORCH_API copy_sparse_to_sparse_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::copy_sparse_to_sparse"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out); +}; + +struct TORCH_API copy_sparse_to_sparse { + 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::copy_sparse_to_sparse"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & src, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, bool non_blocking); +}; + +}} // 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/copysign_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..42bb590428f0a095ed8dbe1e00ae45d1abaa6222 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_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 copysign_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::copysign"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "copysign.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 copysign_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::copysign"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "copysign.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 copysign__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::copysign_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "copysign_.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 copysign_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::copysign"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "copysign.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 copysign__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::copysign_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "copysign_.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 copysign_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::copysign"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "copysign.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/corrcoef_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/corrcoef_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7e825534f18eef559fb2b6267bdb10ad19d19b9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/corrcoef_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 corrcoef(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/cos_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cos_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6a8dacd76b07f5802a1ab0f1ded40117a0fe5982 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/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 cos { + 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::cos"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cos(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 cos_ { + 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::cos_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cos_(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 cos_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::cos"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cos.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/cosh_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosh_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..00f01a9c2a4e82c458d859e80d4d8626647175c4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cosh_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_cosh : 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/count_nonzero.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/count_nonzero.h new file mode 100644 index 0000000000000000000000000000000000000000..eaa9d90b3b8939126d764bd37a14d3db3d3d071e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/count_nonzero.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::count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor +inline at::Tensor count_nonzero(const at::Tensor & self, at::IntArrayRef dim) { + return at::_ops::count_nonzero_dim_IntList::call(self, dim); +} + +// aten::count_nonzero(Tensor self, int? dim=None) -> Tensor +inline at::Tensor count_nonzero(const at::Tensor & self, ::std::optional dim=::std::nullopt) { + return at::_ops::count_nonzero::call(self, dim); +} + +// aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim) { + return at::_ops::count_nonzero_dim_IntList_out::call(self, dim, out); +} +// aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_outf(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { + return at::_ops::count_nonzero_dim_IntList_out::call(self, dim, out); +} + +// aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_out(at::Tensor & out, const at::Tensor & self, ::std::optional dim=::std::nullopt) { + return at::_ops::count_nonzero_out::call(self, dim, out); +} +// aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_outf(const at::Tensor & self, ::std::optional dim, at::Tensor & out) { + return at::_ops::count_nonzero_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/count_nonzero_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/count_nonzero_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..feffc4d9682bded349901099050b33bb739ebcb4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/count_nonzero_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 count_nonzero(const at::Tensor & self, at::IntArrayRef 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/count_nonzero_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/count_nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..22a77be802b2327a8c44718e3b5e356cea9481c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/count_nonzero_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 count_nonzero_dim_IntList { + 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::count_nonzero"; + static constexpr const char* overload_name = "dim_IntList"; + static constexpr const char* schema_str = "count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor"; + 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 count_nonzero { + 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::count_nonzero"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "count_nonzero(Tensor self, int? dim=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim); +}; + +struct TORCH_API count_nonzero_dim_IntList_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::count_nonzero"; + static constexpr const char* overload_name = "dim_IntList_out"; + static constexpr const char* schema_str = "count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +}; + +struct TORCH_API count_nonzero_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::count_nonzero"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional 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/cross_entropy_loss_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cross_entropy_loss_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1bfbcd49c73c4e1b95736675fbdb1945001fe607 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cross_entropy_loss_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 cross_entropy_loss(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100, double label_smoothing=0.0); +TORCH_API at::Tensor cross_entropy_loss_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100, double label_smoothing=0.0); + +} // 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/cross_entropy_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cross_entropy_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f3afbbac21c3e0ea803774a9f41bc5de7c9b526b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cross_entropy_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 cross_entropy_loss_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100, double label_smoothing=0.0); +} // 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/cudnn_batch_norm_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..54e3fcade14d59d751d90345e82c6457214d775e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_batch_norm_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 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); +TORCH_API ::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); +TORCH_API ::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); + +} // 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_add_relu_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_add_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..53b88ca0ed66c6970dc9299e1b83a043c93fa23e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_add_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_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); +TORCH_API at::Tensor cudnn_convolution_add_relu_symint(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, 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_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64cc498945307084221be294631d54fb43da206f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_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 cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); +TORCH_API at::Tensor cudnn_convolution_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32); +TORCH_API at::Tensor & cudnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); +TORCH_API at::Tensor & cudnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out); +TORCH_API at::Tensor & cudnn_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32); +TORCH_API at::Tensor & cudnn_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, 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/cummaxmin_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cummaxmin_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cbc1d3634ac7a6d8396177d2e9ca15966af2aa1a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cummaxmin_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 cummaxmin_backward(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t 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/cumsum_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca75a8b521e73080b170456e5e2ee98b4f0570f4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_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 cumsum(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumsum_out(at::Tensor & out, const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumsum_outf(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor & cumsum_(at::Tensor & self, int64_t dim, ::std::optional 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/cumsum_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..43447fac31da905edf358d851e51141314f312db --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_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 cumsum(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumsum_out(at::Tensor & out, const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumsum_outf(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor & cumsum_(at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); + +} // 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/cumsum_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b57c53b11cf4c3450589da814493d7db03c8cd6f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumsum_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 cumsum { + 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::cumsum"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cumsum(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 cumsum_ { + 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::cumsum_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "cumsum_(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 cumsum_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::cumsum"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "cumsum.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 cumsum_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::cumsum"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "cumsum.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 cumsum__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::cumsum_"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "cumsum_.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 cumsum_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::cumsum"; + static constexpr const char* overload_name = "dimname_out"; + static constexpr const char* schema_str = "cumsum.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/cumulative_trapezoid_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumulative_trapezoid_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5358d2ad146a162f27be346755450a050f762f2d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/cumulative_trapezoid_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 cumulative_trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1); +TORCH_API at::Tensor cumulative_trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-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/dequantize.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize.h new file mode 100644 index 0000000000000000000000000000000000000000..16e0e967be1def46f56b51784dbd887f883fc534 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize.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::dequantize.self(Tensor self) -> Tensor +inline at::Tensor dequantize(const at::Tensor & self) { + return at::_ops::dequantize_self::call(self); +} + +// aten::dequantize.tensors(Tensor[] tensors) -> Tensor[] +inline ::std::vector dequantize(at::TensorList tensors) { + return at::_ops::dequantize_tensors::call(tensors); +} + +// aten::dequantize.self_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & dequantize_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::dequantize_self_out::call(self, out); +} +// aten::dequantize.self_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & dequantize_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::dequantize_self_out::call(self, out); +} + +// aten::dequantize.tensors_out(Tensor[] tensors, *, Tensor(a!)[] out) -> () +inline void dequantize_out(at::TensorList out, at::TensorList tensors) { + return at::_ops::dequantize_tensors_out::call(tensors, out); +} +// aten::dequantize.tensors_out(Tensor[] tensors, *, Tensor(a!)[] out) -> () +inline void dequantize_outf(at::TensorList tensors, at::TensorList out) { + return at::_ops::dequantize_tensors_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/detach_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/detach_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..108c1c9f979fdcff50cf67fbd71b0e80b24c40da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/detach_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 & detach_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & detach_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/diag_embed_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diag_embed_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6e06e34e351877b67e2854a2ec8f7eb8354b8f33 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diag_embed_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 diag_embed(const at::Tensor & self, int64_t offset=0, int64_t dim1=-2, int64_t dim2=-1); + +} // 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/diagonal_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6f4dce76c8be7b2ba4834afb552c20b54d314a51 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_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 diagonal_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, 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::diagonal_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "diagonal_backward(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +}; + +struct TORCH_API diagonal_backward_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, 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::diagonal_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "diagonal_backward.out(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, 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/diagonal_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..49d0dd20e63a151e56b560a46e5920767bc6530d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_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 diagonal(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=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/diagonal_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..533a4230c210783e8f4c64581d777ddbeaf2aa4d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_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 diagonal { + using schema = 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::diagonal"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "diagonal(Tensor(a) self, int offset=0, int dim1=0, int dim2=1) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2); +}; + +struct TORCH_API diagonal_Dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, at::Dimname, at::Dimname, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::diagonal"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "diagonal.Dimname(Tensor(a) self, *, Dimname outdim, Dimname dim1, Dimname dim2, int offset=0) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset); +}; + +}} // 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/diff_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diff_native.h new file mode 100644 index 0000000000000000000000000000000000000000..319d64b667dddfe14dc1be4d2896c17914072652 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/diff_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 diff(const at::Tensor & self, int64_t n=1, int64_t dim=-1, const ::std::optional & prepend={}, const ::std::optional & append={}); +TORCH_API at::Tensor & diff_out(const at::Tensor & self, int64_t n, int64_t dim, const ::std::optional & prepend, const ::std::optional & append, 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/div_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..77e1b5fb3b4a135e0cb04a596b94bb3e59b3a699 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div_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 div(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + +} // 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/div_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..552db574a29bb0ff11db6d63d49a083123727997 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div_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 div(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + +} // 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/div_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4dc6718d0b1ff0c593ffc957f4233ad28cf54749 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/div_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 div(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + +} // 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/dsplit_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b6573be81ebc14f4f2a083515b3f528104e206a7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/dsplit_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 dsplit_int { + using schema = ::std::vector (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::dsplit"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "dsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, int64_t sections); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sections); +}; + +struct TORCH_API dsplit_array { + using schema = ::std::vector (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::dsplit"; + static constexpr const char* overload_name = "array"; + static constexpr const char* schema_str = "dsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, at::IntArrayRef indices); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef indices); +}; + +}} // 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/elu_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..49999385a3cbc4a0c24d6ea31b7f0d9a0b798e82 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_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 elu_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, const at::Scalar &, bool, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::elu_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "elu_backward.grad_input(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(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); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API elu_backward { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &, const at::Scalar &, bool, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::elu_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "elu_backward(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result) -> Tensor"; + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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 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/elu_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2371e7e0290a82ebb508d417e5da94b87e4c5f01 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_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 elu(const at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); +TORCH_API at::Tensor & elu_(at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); + +} // 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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5591bb0150616ee1c6d5dd61e61345e502a8ac35 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/elu_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_elu_out : public at::meta::structured_elu { +void impl(const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, 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/embedding_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d9f436891e31561c8d52ffb82240d2f60c2cc624 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_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_backward(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq, bool sparse); +TORCH_API at::Tensor embedding_backward_symint(const at::Tensor & grad, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse); + +} // 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_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1e8ed804e094673c509ee837a42ee67b560c3656 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_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_backward_symint(const at::Tensor & grad, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse); +} // 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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_bag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f283bd71d600fd5b7cd57ee415fcb6a5550729fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_bag_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 embedding_bag { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::embedding_bag"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API embedding_bag_padding_idx { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::embedding_bag"; + static constexpr const char* overload_name = "padding_idx"; + static constexpr const char* schema_str = "embedding_bag.padding_idx(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, bool include_last_offset, int? padding_idx) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(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, ::std::optional padding_idx); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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, ::std::optional 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/embedding_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7edd358eaad1c14cb03945dfc071d02936b02d38 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_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_symint(const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx=-1, bool scale_grad_by_freq=false, bool sparse=false); +TORCH_API at::Tensor & embedding_out_symint(const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse, at::Tensor & out); +TORCH_API at::Tensor NestedTensor_embedding(const at::Tensor & weight, const at::Tensor & indices, int64_t padding_idx=-1, bool scale_grad_by_freq=false, bool sparse=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/embedding_renorm_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..798b52ae8c248edb065e88043d1de1d9809483eb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_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 embedding_renorm(const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type); +TORCH_API at::Tensor & embedding_renorm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type); +TORCH_API at::Tensor & embedding_renorm_outf(const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_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/embedding_sparse_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_sparse_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..320df2cc5a0be16f7883d99829d3dd03f55c957e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_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_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); +} // 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/empty_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..03c8ba99c56302e4475a52ee9a406ff5915190ad --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_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 & empty_out(at::Tensor & out, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & empty_outf(at::IntArrayRef size, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor & empty_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & empty_symint_outf(c10::SymIntArrayRef size, ::std::optional memory_format, 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/empty_permuted_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_permuted_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..53252068e2498dca2921b4a6b6bcd440e51ae22d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/empty_permuted_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor empty_permuted(at::IntArrayRef size, at::IntArrayRef physical_layout, at::TensorOptions options={}); +TORCH_API at::Tensor empty_permuted(at::IntArrayRef size, at::IntArrayRef physical_layout, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor empty_permuted_symint(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, at::TensorOptions options={}); +TORCH_API at::Tensor empty_permuted_symint(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & empty_permuted_out(at::Tensor & out, at::IntArrayRef size, at::IntArrayRef physical_layout); +TORCH_API at::Tensor & empty_permuted_outf(at::IntArrayRef size, at::IntArrayRef physical_layout, at::Tensor & out); +TORCH_API at::Tensor & empty_permuted_symint_out(at::Tensor & out, c10::SymIntArrayRef size, at::IntArrayRef physical_layout); +TORCH_API at::Tensor & empty_permuted_symint_outf(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, 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/eq_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ccfe775a4893f1cfc5609c1be3ebed611a239d97 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/eq_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 eq(const at::Tensor & self, const at::Scalar & other); +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_(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/equal_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/equal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1dea09cc9afe8ca0f30bee3dc740ffaeb6020003 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/equal_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 equal { + using schema = bool (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::equal"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "equal(Tensor self, Tensor other) -> bool"; + static bool call(const at::Tensor & self, const at::Tensor & other); + static bool 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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9f5d736ada8373fc73bdb2007e241797986712c3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erf_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 erf { + 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::erf"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "erf(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 erf_ { + 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::erf_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "erf_(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 erf_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::erf"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "erf.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/erfc_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..062522781eb7017a15e45a65416d7856a7141c55 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_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 erfc(const at::Tensor & self); +TORCH_API at::Tensor & erfc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erfc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erfc_(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/erfc_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f0638b6f0899ae9905c95107d81a97f7bd76414e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_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 erfc { + 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::erfc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "erfc(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 erfc_ { + 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::erfc_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "erfc_(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 erfc_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::erfc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "erfc.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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a343cd62186fa9959043e911c1953e0438423446 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exp2_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 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::exp2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "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 exp2_ { + 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::exp2_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "exp2_(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 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::exp2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "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/expand.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expand.h new file mode 100644 index 0000000000000000000000000000000000000000..916e3b06cca0cf2038cbfe34db6c6df2f1299281 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expand.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 { + + +namespace symint { + template >> + at::Tensor expand(const at::Tensor & self, at::IntArrayRef size, bool implicit=false) { + return at::_ops::expand::call(self, c10::fromIntArrayRefSlow(size), implicit); + } +} + +namespace symint { + template >> + at::Tensor expand(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit=false) { + return at::_ops::expand::call(self, size, implicit); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expm1_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cfe94bff67dbadc3b707ac885e591e35241429ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/expm1_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_expm1 : 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/exponential.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential.h new file mode 100644 index 0000000000000000000000000000000000000000..1e674891f6f58fe9e099794bee51e883d0562d2f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential.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::exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exponential_out(at::Tensor & out, const at::Tensor & self, double lambd=1, ::std::optional generator=::std::nullopt) { + return at::_ops::exponential_out::call(self, lambd, generator, out); +} +// aten::exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exponential_outf(const at::Tensor & self, double lambd, ::std::optional generator, at::Tensor & out) { + return at::_ops::exponential_out::call(self, lambd, generator, out); +} + +// aten::exponential(Tensor self, float lambd=1, *, Generator? generator=None) -> Tensor +inline at::Tensor exponential(const at::Tensor & self, double lambd=1, ::std::optional generator=::std::nullopt) { + return at::_ops::exponential::call(self, lambd, generator); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6ca604c024131496e7e4018ecdd15cf330e8f600 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_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 & exponential_(at::Tensor & self, double lambd=1, ::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/exponential_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d8b846e13ff56ad45cb9e99bfc371bd843e6fcde --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_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 & exponential_(at::Tensor & self, double lambd=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/exponential_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..71d27d1948f7ab3c1a3c5fe0008d41eddca5a409 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_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 & exponential_(at::Tensor & self, double lambd=1, ::std::optional generator=::std::nullopt); + +} // 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/fake_quantize_per_channel_affine_cachemask.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask.h new file mode 100644 index 0000000000000000000000000000000000000000..b290154ad2895f39cfddf97cd4e14b82604a2225 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask.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::fake_quantize_per_channel_affine_cachemask(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> (Tensor output, Tensor mask) +inline ::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) { + return at::_ops::fake_quantize_per_channel_affine_cachemask::call(self, scale, zero_point, axis, quant_min, quant_max); +} + +// aten::fake_quantize_per_channel_affine_cachemask.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple fake_quantize_per_channel_affine_cachemask_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max) { + return at::_ops::fake_quantize_per_channel_affine_cachemask_out::call(self, scale, zero_point, axis, quant_min, quant_max, out0, out1); +} +// aten::fake_quantize_per_channel_affine_cachemask.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple fake_quantize_per_channel_affine_cachemask_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::fake_quantize_per_channel_affine_cachemask_out::call(self, scale, zero_point, axis, quant_min, quant_max, 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/fake_quantize_per_channel_affine_cachemask_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..07250133c6d1c75049350efb79b032f201f4abda --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_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 fake_quantize_per_channel_affine_cachemask_backward(const at::Tensor & grad, const at::Tensor & mask); + +} // 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/fake_quantize_per_channel_affine_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eff92ec202a491cf02fc0b7e0eb07e8ff9953eff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_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 fake_quantize_per_channel_affine(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 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/fake_quantize_per_tensor_affine_cachemask_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0d84457baa5b99db41514782cd10c44027ba2ea3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_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 fake_quantize_per_tensor_affine_cachemask_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max); +TORCH_API ::std::tuple fake_quantize_per_tensor_affine_cachemask_outf(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, 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/fake_quantize_per_tensor_affine_cachemask_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7370d83912383bc2977dc09a02d1cd48d549205a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_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_per_tensor_affine_cachemask(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_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/fbgemm_linear_fp16_weight_fp32_activation_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fc52639a98792a4a53b23b1aaa179fca54984825 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_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_linear_fp16_weight_fp32_activation(const at::Tensor & input, const at::Tensor & packed_weight, const ::std::optional & bias); +TORCH_API at::Tensor fbgemm_linear_fp16_weight_fp32_activation(const at::Tensor & input, const at::Tensor & packed_weight, const ::std::optional & bias, 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/fbgemm_linear_quantize_weight.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..a7c8bc07e257421934e29dadd95b5f763705d92b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_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_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int) +inline ::std::tuple fbgemm_linear_quantize_weight(const at::Tensor & input) { + return at::_ops::fbgemm_linear_quantize_weight::call(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/fbgemm_pack_gemm_matrix_fp16_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff0a9fb1d3e79d6994759d01e7438959b9cb2ced --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_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 fbgemm_pack_gemm_matrix_fp16(const at::Tensor & input); + +} // 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/feature_dropout_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c395e36791a04e25ec356b221aa79eff5c7aaef7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_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 feature_dropout(const at::Tensor & input, double p, bool train); +TORCH_API at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train); +} // 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_fft2_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e6cb5c6afeb0bd38fe972761530cc5fb0edc03ed --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_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_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_fft2_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_fft2_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_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_fft2_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_fft2_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_fftfreq_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ab57e3f623f85d0d8285d3287a576fa81865bb27 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_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_fftfreq(int64_t n, double d=1.0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & fft_fftfreq_out(int64_t n, double d, 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_fftn.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn.h new file mode 100644 index 0000000000000000000000000000000000000000..63b1c9f7fd0ecaad0bca4eaae0b150b936a11601 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn.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_fftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_fftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_fftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_fftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_fftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fftn::call(self, s, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_fftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fftn::call(self, s, dim, norm); + } +} + +// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fftn_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_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_fftn_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_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fftn_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_fftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_fftn_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_fftn_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fftn_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_fftn_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fc220aa1601ca698dcbb0286e88310bb615ea333 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_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_fftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_fftn_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_fftn_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_fftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_fftn_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_fftn_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_hfft2_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..445c47ce0bf6ab5737b589c2deeb6facad9cab00 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_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_hfft2_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_hfft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef 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_ifftn_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d0c756e3d7cfce6411faf5c331cd86ecb63aee2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifftn_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_ifftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_ifftn_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_ifftn_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_ifftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_ifftn_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_ifftn_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_ihfftn_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..91e36b652335fec8d42bff4f90f9347e81cf8f2d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn_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_ihfftn { + 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_ihfftn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_ihfftn(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_ihfftn_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_ihfftn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_ihfftn.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_irfft_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft_native.h new file mode 100644 index 0000000000000000000000000000000000000000..62d682fcd775bbc2d7cd96ed1e526e2b63e6a626 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfft_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_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_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_irfftn.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfftn.h new file mode 100644 index 0000000000000000000000000000000000000000..7a41423359b257505e01a28f62803db02ec835f2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_irfftn.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_irfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_irfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_irfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_irfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_irfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_irfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_irfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_irfftn::call(self, s, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_irfftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_irfftn::call(self, s, dim, norm); + } +} + +// aten::fft_irfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_irfftn_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_irfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_irfftn_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_irfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_irfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_irfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_irfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_irfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_irfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_irfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_irfftn_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_irfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_irfftn_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_irfftn_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_irfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_irfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_irfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_irfftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_irfftn_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_rfftfreq.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq.h new file mode 100644 index 0000000000000000000000000000000000000000..eaeaefe2daa2dd643f4d93d46b6b63db38f9310c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq.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_rfftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor fft_rfftfreq(int64_t n, double d=1.0, at::TensorOptions options={}) { + return at::_ops::fft_rfftfreq::call(n, d, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::fft_rfftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor fft_rfftfreq(int64_t n, double d, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::fft_rfftfreq::call(n, d, dtype, layout, device, pin_memory); +} + +// aten::fft_rfftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfftfreq_out(at::Tensor & out, int64_t n, double d=1.0) { + return at::_ops::fft_rfftfreq_out::call(n, d, out); +} +// aten::fft_rfftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfftfreq_outf(int64_t n, double d, at::Tensor & out) { + return at::_ops::fft_rfftfreq_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_rfftfreq_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a72eab406e2628f773c4dfafd1cdc9a10c8bc5c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftfreq_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 fft_rfftfreq(int64_t n, double d=1.0, at::TensorOptions options={}); +TORCH_API at::Tensor fft_rfftfreq(int64_t n, double d, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & fft_rfftfreq_out(at::Tensor & out, int64_t n, double d=1.0); +TORCH_API at::Tensor & fft_rfftfreq_outf(int64_t n, double d, 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/fft_rfftn_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..48862529779a2becfcf8475a4e35c3b7c6847b51 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn_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_rfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +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_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_rfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_rfftn_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_rfftn_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/flip.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flip.h new file mode 100644 index 0000000000000000000000000000000000000000..bda6b6e1be3312d126f180fd5a18f90762a98cf1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flip.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::flip(Tensor self, int[] dims) -> Tensor +inline at::Tensor flip(const at::Tensor & self, at::IntArrayRef dims) { + return at::_ops::flip::call(self, dims); +} + +// aten::flip.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & flip_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dims) { + return at::_ops::flip_out::call(self, dims, out); +} +// aten::flip.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & flip_outf(const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out) { + return at::_ops::flip_out::call(self, 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/flipud_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_native.h new file mode 100644 index 0000000000000000000000000000000000000000..62ac58880aaccbd749d0b46163f20f0090a3776e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_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 flipud(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/float_power.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/float_power.h new file mode 100644 index 0000000000000000000000000000000000000000..21702ed8a99ee788fd0f33b29058762c5dcc6d3e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/float_power.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::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & exponent) { + return at::_ops::float_power_Tensor_Tensor_out::call(self, exponent, out); +} +// aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_outf(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) { + return at::_ops::float_power_Tensor_Tensor_out::call(self, exponent, out); +} + +// aten::float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor +inline at::Tensor float_power(const at::Tensor & self, const at::Tensor & exponent) { + return at::_ops::float_power_Tensor_Tensor::call(self, exponent); +} + +// aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & exponent) { + return at::_ops::float_power_Scalar_out::call(self, exponent, out); +} +// aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_outf(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) { + return at::_ops::float_power_Scalar_out::call(self, exponent, out); +} + +// aten::float_power.Scalar(Scalar self, Tensor exponent) -> Tensor +inline at::Tensor float_power(const at::Scalar & self, const at::Tensor & exponent) { + return at::_ops::float_power_Scalar::call(self, exponent); +} + +// aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & exponent) { + return at::_ops::float_power_Tensor_Scalar_out::call(self, exponent, out); +} +// aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_outf(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) { + return at::_ops::float_power_Tensor_Scalar_out::call(self, exponent, out); +} + +// aten::float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor +inline at::Tensor float_power(const at::Tensor & self, const at::Scalar & exponent) { + return at::_ops::float_power_Tensor_Scalar::call(self, exponent); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frac_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..73e47f448f188bbfc46cc5a524f20c6df553ee20 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frac_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 frac { + 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::frac"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "frac(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 frac_ { + 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::frac_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "frac_(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 frac_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::frac"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "frac.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/frexp_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d93cda66b1f05de8748ad688402ccbbc9909cdff --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_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 frexp_Tensor { + using schema = ::std::tuple (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::frexp"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "frexp.Tensor(Tensor self) -> (Tensor mantissa, Tensor exponent)"; + static ::std::tuple call(const at::Tensor & self); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API frexp_Tensor_out { + using schema = ::std::tuple (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::frexp"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "frexp.Tensor_out(Tensor self, *, Tensor(a!) mantissa, Tensor(b!) exponent) -> (Tensor(a!) mantissa, Tensor(b!) exponent)"; + static ::std::tuple call(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent); +}; + +}} // 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..4c2eeb3131d5af28232b8fb4e2530ce1f503a936 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_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::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor +inline at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false) { + return at::_ops::frobenius_norm_dim::call(self, dim, keepdim); +} + +// aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & frobenius_norm_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false) { + return at::_ops::frobenius_norm_out::call(self, dim, keepdim, out); +} +// aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & frobenius_norm_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { + return at::_ops::frobenius_norm_out::call(self, dim, keepdim, 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/full_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/full_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64fcf1b0e9145332205f76613719f83309c0e6ad --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/full_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 full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names); +TORCH_API at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}); +TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}); +TORCH_API at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value); +TORCH_API at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out); +TORCH_API at::Tensor & full_symint_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Scalar & fill_value); +TORCH_API at::Tensor & full_symint_outf(c10::SymIntArrayRef size, const at::Scalar & fill_value, 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/fused_moving_avg_obs_fake_quant_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9b6e5cfcbfe56b587ad7a209413c031c52485ce1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_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 fused_moving_avg_obs_fake_quant(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=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/gather_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..03c272f37d288a1ee66e366db902e749c9b18878 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gather_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 gather_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gather_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "gather_backward(Tensor grad, Tensor self, int dim, Tensor index, bool sparse_grad) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_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/gelu_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..40fd9ec6abcecc734b85e7e4237da42ca06a8ad6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_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 gelu_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gelu_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input); +}; + +struct TORCH_API gelu_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gelu_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate); +}; + +}} // 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/gelu_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4698e6a5ea07cd8ffbd26afdb8edc55e254fe97a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_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 gelu(const at::Tensor & self, c10::string_view approximate="none"); +TORCH_API at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self, c10::string_view approximate="none"); +TORCH_API at::Tensor & gelu_outf(const at::Tensor & self, c10::string_view approximate, at::Tensor & out); +TORCH_API at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none"); + +} // 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/geqrf.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf.h new file mode 100644 index 0000000000000000000000000000000000000000..156ac82717bb067607431126b04ada636d0ca663 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf.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::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) +inline ::std::tuple geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self) { + return at::_ops::geqrf_a::call(self, a, tau); +} +// aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) +inline ::std::tuple geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau) { + return at::_ops::geqrf_a::call(self, a, tau); +} + +// aten::geqrf(Tensor self) -> (Tensor a, Tensor tau) +inline ::std::tuple geqrf(const at::Tensor & self) { + return at::_ops::geqrf::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/ger_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2b02a7b9b496e68a9e8bdaa2239ee7c686bf4d15 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ger_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 ger { + 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::ger"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ger(Tensor self, Tensor vec2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & vec2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2); +}; + +struct TORCH_API ger_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::ger"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2, 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/glu_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..d2fb182f5ac60353b4b2676152361b208efeaaa8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_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::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & glu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim) { + return at::_ops::glu_backward_grad_input::call(grad_output, self, dim, grad_input); +} +// aten::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & glu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input) { + return at::_ops::glu_backward_grad_input::call(grad_output, self, dim, grad_input); +} + +// aten::glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor +inline at::Tensor glu_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim) { + return at::_ops::glu_backward::call(grad_output, self, 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/glu_backward_jvp_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..edcdaa1204dded4288ac84b1f1618507f118db35 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_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 glu_backward_jvp(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, 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/glu_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..76f5c436d606768910131e9f9bb1b76b20229300 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_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 at::Tensor glu_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & glu_backward_cpu_out(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input); +TORCH_API at::Tensor glu_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & glu_backward_cuda_out(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, 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/glu_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd9430baf18c023e8915c647388e18929acdce78 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/glu_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 glu(const at::Tensor & self, int64_t dim=-1); + +} // 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/greater_equal_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c586185bf19c31229dc4ac747b587d7cee37cccf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_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 greater_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_equal_out(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(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 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d.h new file mode 100644 index 0000000000000000000000000000000000000000..1de25774a3c9a51b86e84502e3b7f99778a8a2b2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d.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(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor +inline at::Tensor grid_sampler_2d(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::call(input, grid, interpolation_mode, padding_mode, align_corners); +} + +// aten::grid_sampler_2d.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_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_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} +// aten::grid_sampler_2d.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_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_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_3d_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3de7e3ae1cdfab5b1af6ff5ceceb438e8e00216 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_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 grid_sampler_3d_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); + +} // 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/gru.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru.h new file mode 100644 index 0000000000000000000000000000000000000000..49e4b8aacaf10f6f8c487f8c95bdd3ba1a33dae3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru.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::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) +inline ::std::tuple gru(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::gru_input::call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); +} + +// aten::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) +inline ::std::tuple gru(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::gru_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/gru_cell_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e01b35bb5fd99bfe8d7e0b175828869b66a0d52 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/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 gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_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/gru_cell_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4733a6271a998a8fcad8cf60243970e8a72c5b3b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gru_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 at::Tensor gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_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/gt_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2adf4413ad719330df8f8e27ddfb2f606cb7404f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_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 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 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/gt_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..b2c107abe00a6f7551b65dd8e5946f01764f856c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_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_gt_Scalar : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & other); +}; +struct TORCH_API structured_gt_Tensor : 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/gt_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4499fba0e50cf7fe81214832e840943adef800a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/gt_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 gt_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::gt"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "gt.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 gt_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::gt"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "gt.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 gt_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::gt"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "gt.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 gt_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::gt"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "gt.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 gt__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::gt_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "gt_.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 gt__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::gt_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "gt_.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/hamming_window.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window.h new file mode 100644 index 0000000000000000000000000000000000000000..645fdfc8140c9b83d0e27943dee2d36ee386614d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window.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 { + + +// aten::hamming_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor hamming_window(int64_t window_length, at::TensorOptions options={}) { + return at::_ops::hamming_window::call(window_length, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::hamming_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor hamming_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::hamming_window::call(window_length, dtype, layout, device, pin_memory); +} + +// aten::hamming_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor hamming_window(int64_t window_length, bool periodic, at::TensorOptions options={}) { + return at::_ops::hamming_window_periodic::call(window_length, periodic, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::hamming_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor hamming_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::hamming_window_periodic::call(window_length, periodic, dtype, layout, device, pin_memory); +} + +// aten::hamming_window.periodic_alpha(int window_length, bool periodic, float alpha, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, at::TensorOptions options={}) { + return at::_ops::hamming_window_periodic_alpha::call(window_length, periodic, alpha, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::hamming_window.periodic_alpha(int window_length, bool periodic, float alpha, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::hamming_window_periodic_alpha::call(window_length, periodic, alpha, dtype, layout, device, pin_memory); +} + +// aten::hamming_window.periodic_alpha_beta(int window_length, bool periodic, float alpha, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, at::TensorOptions options={}) { + return at::_ops::hamming_window_periodic_alpha_beta::call(window_length, periodic, alpha, beta, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::hamming_window.periodic_alpha_beta(int window_length, bool periodic, float alpha, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::hamming_window_periodic_alpha_beta::call(window_length, periodic, alpha, beta, dtype, layout, device, pin_memory); +} + +// aten::hamming_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length) { + return at::_ops::hamming_window_out::call(window_length, out); +} +// aten::hamming_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_outf(int64_t window_length, at::Tensor & out) { + return at::_ops::hamming_window_out::call(window_length, out); +} + +// aten::hamming_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic) { + return at::_ops::hamming_window_periodic_out::call(window_length, periodic, out); +} +// aten::hamming_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, at::Tensor & out) { + return at::_ops::hamming_window_periodic_out::call(window_length, periodic, out); +} + +// aten::hamming_window.periodic_alpha_out(int window_length, bool periodic, float alpha, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha) { + return at::_ops::hamming_window_periodic_alpha_out::call(window_length, periodic, alpha, out); +} +// aten::hamming_window.periodic_alpha_out(int window_length, bool periodic, float alpha, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, at::Tensor & out) { + return at::_ops::hamming_window_periodic_alpha_out::call(window_length, periodic, alpha, out); +} + +// aten::hamming_window.periodic_alpha_beta_out(int window_length, bool periodic, float alpha, float beta, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha, double beta) { + return at::_ops::hamming_window_periodic_alpha_beta_out::call(window_length, periodic, alpha, beta, out); +} +// aten::hamming_window.periodic_alpha_beta_out(int window_length, bool periodic, float alpha, float beta, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out) { + return at::_ops::hamming_window_periodic_alpha_beta_out::call(window_length, periodic, alpha, beta, 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/hamming_window_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..01384fc4bf07e097ec8358bcf24475f212f1411d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_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 hamming_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::hamming_window"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hamming_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 hamming_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::hamming_window"; + static constexpr const char* overload_name = "periodic"; + static constexpr const char* schema_str = "hamming_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 hamming_window_periodic_alpha { + 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::hamming_window"; + static constexpr const char* overload_name = "periodic_alpha"; + static constexpr const char* schema_str = "hamming_window.periodic_alpha(int window_length, bool periodic, float alpha, *, 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 alpha, ::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 alpha, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API hamming_window_periodic_alpha_beta { + using schema = at::Tensor (int64_t, bool, double, 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::hamming_window"; + static constexpr const char* overload_name = "periodic_alpha_beta"; + static constexpr const char* schema_str = "hamming_window.periodic_alpha_beta(int window_length, bool periodic, float alpha, 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 alpha, 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 alpha, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API hamming_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::hamming_window"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hamming_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 hamming_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::hamming_window"; + static constexpr const char* overload_name = "periodic_out"; + static constexpr const char* schema_str = "hamming_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 hamming_window_periodic_alpha_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::hamming_window"; + static constexpr const char* overload_name = "periodic_alpha_out"; + static constexpr const char* schema_str = "hamming_window.periodic_alpha_out(int window_length, bool periodic, float alpha, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t window_length, bool periodic, double alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double alpha, at::Tensor & out); +}; + +struct TORCH_API hamming_window_periodic_alpha_beta_out { + using schema = at::Tensor & (int64_t, bool, double, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hamming_window"; + static constexpr const char* overload_name = "periodic_alpha_beta_out"; + static constexpr const char* schema_str = "hamming_window.periodic_alpha_beta_out(int window_length, bool periodic, float alpha, float beta, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double alpha, 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/hardshrink_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..184b238d23b4d2b51c8e1d067da6f25f47ce2943 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_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::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd) { + return at::_ops::hardshrink_backward_grad_input::call(grad_out, self, lambd, grad_input); +} +// aten::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) { + return at::_ops::hardshrink_backward_grad_input::call(grad_out, self, lambd, grad_input); +} + +// aten::hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor +inline at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd) { + return at::_ops::hardshrink_backward::call(grad_out, self, lambd); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4cd781018ad45531f9286ec31bc19eac759b7f6d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_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 hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); +TORCH_API at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); +TORCH_API at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, 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/hardshrink_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4570853b54700b556d772b0a5042c804b970c692 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_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 hardshrink_backward_grad_input { + using schema = 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::hardshrink_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input); +}; + +struct TORCH_API hardshrink_backward { + using schema = 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::hardshrink_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); +}; + +}} // 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_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a99653bede0c388d7bde174f177fcfc88a4d779a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_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 hardsigmoid_backward(const at::Tensor & grad_output, 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/hardsigmoid_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..15db8ec37ea2ae05a9230eba5157be57dc4a6369 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_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 hardsigmoid_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::hardsigmoid"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hardsigmoid.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 hardsigmoid { + 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::hardsigmoid"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardsigmoid(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 hardsigmoid_ { + 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::hardsigmoid_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardsigmoid_(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/hardswish_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cb4876798e09627e3b9e1d178d73a70c2163a48e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_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 hardswish_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::hardswish"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hardswish.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 hardswish { + 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::hardswish"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardswish(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 hardswish_ { + 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::hardswish_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardswish_(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/hardtanh_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b51f3b5cdc08f615e99ef9e88427a3fdf2687df --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_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 hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1); +TORCH_API at::Tensor & hardtanh_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1); +TORCH_API at::Tensor & hardtanh_outf(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out); +TORCH_API at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=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/hash_tensor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hash_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..0d8fcbfb2f50fb9d0cb57210fd7e541224bfccf1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hash_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::hash_tensor(Tensor self, int[1] dim=[], *, bool keepdim=False, int mode=0) -> Tensor +inline at::Tensor hash_tensor(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false, int64_t mode=0) { + return at::_ops::hash_tensor::call(self, dim, keepdim, mode); +} + +// aten::hash_tensor.out(Tensor self, int[1] dim=[], *, bool keepdim=False, int mode=0, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hash_tensor_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false, int64_t mode=0) { + return at::_ops::hash_tensor_out::call(self, dim, keepdim, mode, out); +} +// aten::hash_tensor.out(Tensor self, int[1] dim=[], *, bool keepdim=False, int mode=0, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hash_tensor_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, int64_t mode, at::Tensor & out) { + return at::_ops::hash_tensor_out::call(self, dim, keepdim, 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/hash_tensor_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hash_tensor_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..949734bd6357011f94edcc23e2813d7c78660871 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hash_tensor_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_hash_tensor : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, int64_t 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/heaviside_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8830ec9992f72c015bf6c9d66e76cdbf561ba9aa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_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 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 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/histc_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8c31998cf026705f8cb46a976d07ce3506d4dd08 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histc_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 histc(const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); +TORCH_API at::Tensor & histc_out(at::Tensor & out, const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); +TORCH_API at::Tensor & histc_outf(const at::Tensor & self, int64_t bins, const at::Scalar & min, const at::Scalar & max, 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/histogramdd.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogramdd.h new file mode 100644 index 0000000000000000000000000000000000000000..baec7c409a6186beae4d6525ad43f72af51f3e7a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogramdd.h @@ -0,0 +1,46 @@ +#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::histogramdd(Tensor self, int[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) +inline ::std::tuple> histogramdd(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::histogramdd::call(self, bins, range, weight, density); +} + +// aten::histogramdd.int_bins(Tensor self, int bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) +inline ::std::tuple> histogramdd(const at::Tensor & self, int64_t bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::histogramdd_int_bins::call(self, bins, range, weight, density); +} + +// aten::histogramdd.TensorList_bins(Tensor self, Tensor[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) +inline ::std::tuple> histogramdd(const at::Tensor & self, at::TensorList bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::histogramdd_TensorList_bins::call(self, bins, range, weight, density); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79f0407cf20d6d9c3128fb83f840d5d6ea5ad136 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/histogramdd_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> histogramdd(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, int64_t bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, at::TensorList bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=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/huber_loss_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3fe012257513ccf4395b46d6562df8e48f1140e3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_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 & 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 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/huber_loss_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4f8469dbe84c28ed3649d4381679da9283e59e39 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/huber_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 huber_loss_backward(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_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, 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/hypot_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b021b52c9797a706b7cd0c279d66ee6cd8b16cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_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 hypot(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & hypot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & hypot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & hypot_(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/hypot_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..bbafecd16bf155744c501d5f23ac031e016d30f1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_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_hypot : 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/hypot_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d1c73bd42cacf17bc4b6f11174d190f1ba39bed2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_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_hypot_out : public at::meta::structured_hypot { +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/hypot_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..406a0a28c362736721060519f7deb8bfe7444999 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_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 hypot_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::hypot"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hypot.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 hypot { + 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::hypot"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hypot(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 hypot_ { + 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::hypot_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hypot_(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/i0_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c09e460393c08a6106f6f7d39a1a401d32bdf01d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0_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_i0_out : public at::meta::structured_i0 { +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/i0_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fb580ba0e782be60ea17d788df824cf576946235 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/i0_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 i0 { + 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::i0"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "i0(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 i0_ { + 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::i0_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "i0_(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 i0_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::i0"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "i0.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/igamma.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma.h new file mode 100644 index 0000000000000000000000000000000000000000..ad3cd24bb0b7e339b24721fbe94413dae8a5cdd9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma.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::igamma.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & igamma_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::igamma_out::call(self, other, out); +} +// aten::igamma.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & igamma_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::igamma_out::call(self, other, out); +} + +// aten::igamma(Tensor self, Tensor other) -> Tensor +inline at::Tensor igamma(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::igamma::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/igamma_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..80fa78b9ac5b8c132308761013bff2149d8b7d9f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_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 igamma(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_(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/igamma_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a0f88d60642d8ee907ea208e56f2a5afc64048fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_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 igamma(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & igamma_(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/igamma_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0fae9d8ae6442010a8c6a995106e331c47c88153 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_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 igamma(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & igamma_(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/igammac_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bed4df6fea2a8e636f66a2b7071bf21388ff9f4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_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 igammac(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igammac_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igammac_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & igammac_(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/igammac_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..96f230a6e636289fb18ea717a13bc60f972f625a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_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 igammac(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igammac_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igammac_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & igammac_(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/igammac_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82b67bf3dc3a823c562f7e6311088b306a5da43a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_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_igammac_out : public at::meta::structured_igammac { +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/im2col_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/im2col_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b5f30819d91d526d2ebc733ee645fc2a3b3cc028 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/im2col_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 im2col(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & im2col_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & im2col_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, 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/imag_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/imag_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4b2f3a1615bfabd91c9e811d69737ae8cf522e29 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/imag_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 imag(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/index_add_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..26e5322540d979904bdec1516fac8be51140415d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_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 index_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); + +} // 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/index_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3863b2dea4544d4d8838eb15319ee57dde5fbbe8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_copy_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 index_copy_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, 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::index_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "index_copy.out(Tensor self, int dim, Tensor index, Tensor source, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, at::Tensor & out); +}; + +struct TORCH_API index_copy_ { + using schema = at::Tensor & (at::Tensor &, int64_t, 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::index_copy_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_copy_(Tensor(a!) self, int dim, Tensor index, Tensor source) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); +}; + +struct TORCH_API index_copy { + using schema = at::Tensor (const at::Tensor &, int64_t, 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::index_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_copy(Tensor self, int dim, Tensor index, Tensor source) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); +}; + +struct TORCH_API index_copy__dimname { + using schema = at::Tensor & (at::Tensor &, at::Dimname, 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::index_copy_"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); +}; + +struct TORCH_API index_copy_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, 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::index_copy"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); +}; + +}} // 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/index_fill_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_fill_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bfbab7ecd83830780e2d475e7aae39fc7267d03a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_fill_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 & 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 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/index_reduce_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ff08fe20857f4d3883bc779be7a439c29a397a43 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_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_index_reduce_cpu_out : public at::meta::structured_index_reduce { +void impl(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self, const at::Tensor & out); +}; +struct TORCH_API structured_index_reduce_cuda_out : public at::meta::structured_index_reduce { +void impl(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_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/index_select_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7840fb3d2833153485767b27ba23f90f23fff63f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_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 index_select_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef self_sizes, int64_t dim, const at::Tensor & index); +} // 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_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6eb9ba8ff3c5643166faafeba5015c37159ca076 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_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 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 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/inner_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/inner_native.h new file mode 100644 index 0000000000000000000000000000000000000000..80aa48672f3ecb50687ba0f6ad8ba1121b2d892a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/inner_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 inner(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & inner_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/inverse_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/inverse_native.h new file mode 100644 index 0000000000000000000000000000000000000000..01fba486a2c1a228f7b5638e374c9ad39592ef0d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/inverse_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 inverse(const at::Tensor & self); +TORCH_API at::Tensor & inverse_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/is_complex_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_complex_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f8eefda8e77c14aaf26546fdc0ce1b189a82915f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_complex_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 is_complex(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/is_conj.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_conj.h new file mode 100644 index 0000000000000000000000000000000000000000..4765915daa6d3ffd961ffba8d4cac2106d50d04c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_conj.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::is_conj(Tensor self) -> bool +inline bool __dispatch_is_conj(const at::Tensor & self) { + return at::_ops::is_conj::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/is_inference.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_inference.h new file mode 100644 index 0000000000000000000000000000000000000000..d1f8d70b40e8aadb64ac4e75739a99b4d7118dbf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_inference.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::is_inference(Tensor self) -> bool +inline bool __dispatch_is_inference(const at::Tensor & self) { + return at::_ops::is_inference::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/is_leaf_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_leaf_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f67d34541cd92b3d428d2100e4413883d59f6aa3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_leaf_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 is_leaf(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/is_nonzero_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_nonzero_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5528b777646016b5895f809c1089989b2cab85ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_nonzero_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 is_nonzero(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/is_nonzero_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e455790b6dbecfd5dcd35f586c0d2f6a82793202 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_nonzero_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_nonzero { + 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_nonzero"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "is_nonzero(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_same_size.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size.h new file mode 100644 index 0000000000000000000000000000000000000000..a4d05b9f89cb524c02e60fcc6b0496d7d14a63c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_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::is_same_size(Tensor self, Tensor other) -> bool +inline bool is_same_size(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::is_same_size::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/is_set_to_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_set_to_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7a5d1e32a9b9c9650d396f20b903990f996c4d4a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_set_to_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 bool is_set_to(const at::Tensor & self, const at::Tensor & tensor); + +} // 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/is_signed_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_signed_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d25b945e3011ba4702258440c2d7931321fafdf6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_signed_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_signed { + 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_signed"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "is_signed(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_vulkan_available_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_vulkan_available_native.h new file mode 100644 index 0000000000000000000000000000000000000000..88d8e0c1c6e4d533284f4bde25961c109837b146 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/is_vulkan_available_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_vulkan_available(); +} // 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/isin_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isin_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e01a0da238674a82cf48b974a58cd75ece05ce8b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isin_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 isin(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_outf(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out); +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_out(at::Tensor & out, const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_outf(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert, at::Tensor & out); +TORCH_API at::Tensor isin(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_outf(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert, 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/isnan_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isnan_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fd053bad56fe4037a2092759b7929a146e5d85d7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isnan_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 & isnan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & isnan_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/isneginf.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isneginf.h new file mode 100644 index 0000000000000000000000000000000000000000..183cc447c72e241255f9fc94f624df47d8510caf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/isneginf.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::isneginf(Tensor self) -> Tensor +inline at::Tensor isneginf(const at::Tensor & self) { + return at::_ops::isneginf::call(self); +} + +// aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::isneginf_out::call(self, out); +} +// aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::isneginf_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/istft_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/istft_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5b56b7b5304ef9d0da2f8abe99149c450eafab55 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/istft_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 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); + +} // 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/kron_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kron_native.h new file mode 100644 index 0000000000000000000000000000000000000000..da613d415d416783288173fb953debcc4c9b47fb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kron_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 kron(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & kron_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/kthvalue_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ecb1e8090ee931bc7360c666b3acafc80ade1a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_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 kthvalue(const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool keepdim=false); + +} // 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/kthvalue_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_native.h new file mode 100644 index 0000000000000000000000000000000000000000..981a26bdb5ebe84f7fdb29b5ff8b7c6b503412db --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/kthvalue_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::tuple kthvalue(const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_out_cpu(const at::Tensor & self, int64_t k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple kthvalue_out_cuda(const at::Tensor & self, int64_t k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple kthvalue(const at::Tensor & self, int64_t k, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple kthvalue_out(const at::Tensor & self, int64_t k, 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/lcm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lcm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1bf06e75578da55bbedc3a5f83b6d649bef288d6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lcm_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_lcm_out : public at::meta::structured_lcm { +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/ldexp_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ldexp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ded3b02e5d1a1df50808ed64ab3fa26a99998822 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ldexp_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 ldexp_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::ldexp"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "ldexp.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 ldexp_ { + 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::ldexp_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ldexp_(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 ldexp_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::ldexp"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "ldexp.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/leaky_relu_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..da801d99043f187ca0fc5e3e97def4e14d3ea368 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_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::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::leaky_relu_backward_grad_input::call(grad_output, self, negative_slope, self_is_result, grad_input); +} +// aten::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::leaky_relu_backward_grad_input::call(grad_output, self, negative_slope, self_is_result, grad_input); +} + +// aten::leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor +inline at::Tensor leaky_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result) { + return at::_ops::leaky_relu_backward::call(grad_output, self, negative_slope, self_is_result); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..980ab71dd097db1f3d81166361d591551830f0ba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_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 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 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/leaky_relu_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..8c3078d30ee3e27cf4eb770483d150e23ee4b352 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_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_leaky_relu_backward : public TensorIteratorBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); +}; + +} // 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/leaky_relu_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..48422eac537f670fbd6dfcc267862c745f2464fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_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 leaky_relu(const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_outf(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out); +TORCH_API at::Tensor & leaky_relu_(at::Tensor & self, const at::Scalar & negative_slope=0.01); + +} // 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/lerp_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0393c817a767e17b9e5b35a1cbe7d065ca048874 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_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 lerp__Scalar { + using schema = at::Tensor & (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::lerp_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "lerp_.Scalar(Tensor(a!) self, Tensor end, Scalar weight) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +}; + +struct TORCH_API lerp__Tensor { + using schema = at::Tensor & (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::lerp_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "lerp_.Tensor(Tensor(a!) self, Tensor end, Tensor weight) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +}; + +struct TORCH_API lerp_Scalar_out { + using schema = 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::lerp"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "lerp.Scalar_out(Tensor self, Tensor end, Scalar weight, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, at::Tensor & out); +}; + +struct TORCH_API lerp_Tensor_out { + using schema = at::Tensor & (const 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::lerp"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "lerp.Tensor_out(Tensor self, Tensor end, Tensor weight, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, at::Tensor & out); +}; + +struct TORCH_API lerp_Scalar { + using schema = 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::lerp"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "lerp.Scalar(Tensor self, Tensor end, Scalar weight) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +}; + +struct TORCH_API lerp_Tensor { + using schema = 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::lerp"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "lerp.Tensor(Tensor self, Tensor end, Tensor weight) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, 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/less.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less.h new file mode 100644 index 0000000000000000000000000000000000000000..556d4b05b42e00dedeaff19ef2fa7e2eb1c92717 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less.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.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::less_Scalar_out::call(self, other, out); +} +// aten::less.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::less_Scalar_out::call(self, other, out); +} + +// aten::less.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor less(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::less_Scalar::call(self, other); +} + +// aten::less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::less_Tensor_out::call(self, other, out); +} +// aten::less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & less_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::less_Tensor_out::call(self, other, out); +} + +// aten::less.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor less(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::less_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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_native.h new file mode 100644 index 0000000000000000000000000000000000000000..733fb3d0d11dcfc0a60f41ec6a94c7d2a4fb04e1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/less_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 less(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & less_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & less_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor less(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & less_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & less_(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/lgamma_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..55030431a4d4f204a306909f89ab381d44f00277 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_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 lgamma(const at::Tensor & self); +TORCH_API at::Tensor & lgamma_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & lgamma_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & lgamma_(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/lgamma_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5b7967e4ed4d2c21808b00f6f3fe60d7a101dd0d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_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 lgamma_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::lgamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "lgamma.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 lgamma_ { + 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::lgamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "lgamma_(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 lgamma { + 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::lgamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "lgamma(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/lift_fresh_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d8f97f480dab412702b35072fbf97223d08301a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_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 lift_fresh(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/lift_fresh_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ed10afe3c577e8e58e727d3abc175ae43cd8acda --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_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 & lift_fresh_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor lift_fresh_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/lift_fresh_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..09eac204a29308dbcfedeea340c60b5ae6e57583 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lift_fresh_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 lift_fresh(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/linalg_cholesky_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72d1df74bb115df1e4e50e3263336508f9d53193 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_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_cholesky(const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & linalg_cholesky_out(at::Tensor & out, const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & linalg_cholesky_outf(const at::Tensor & self, bool upper, 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_cholesky_ex_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9a5ed742fa9b2cf2470251306fd963bcac0a91f1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_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_cholesky_ex(const at::Tensor & self, bool upper=false, 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_cholesky_ex_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5245fc8450bb1106ff5846f4156af8b43e705f6a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_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_cholesky_ex(const at::Tensor & self, bool upper=false, bool check_errors=false); +TORCH_API ::std::tuple linalg_cholesky_ex_out(at::Tensor & L, at::Tensor & info, const at::Tensor & self, bool upper=false, bool check_errors=false); +TORCH_API ::std::tuple linalg_cholesky_ex_outf(const at::Tensor & self, bool upper, bool check_errors, at::Tensor & L, at::Tensor & info); + +} // 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_cholesky_ex_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5baad440f9a777ff51e6be9e8068c1a09f779ba4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_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_cholesky_ex_out : public at::meta::structured_linalg_cholesky_ex { +void impl(const at::Tensor & self, bool upper, bool check_errors, const at::Tensor & L, 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_cond.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond.h new file mode 100644 index 0000000000000000000000000000000000000000..7a7f5f8691625aff5c30eeb0d26c51858c153c8a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond.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_cond(Tensor self, Scalar? p=None) -> Tensor +inline at::Tensor linalg_cond(const at::Tensor & self, const ::std::optional & p=::std::nullopt) { + return at::_ops::linalg_cond::call(self, p); +} + +// aten::linalg_cond.out(Tensor self, Scalar? p=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p=::std::nullopt) { + return at::_ops::linalg_cond_out::call(self, p, out); +} +// aten::linalg_cond.out(Tensor self, Scalar? p=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_outf(const at::Tensor & self, const ::std::optional & p, at::Tensor & out) { + return at::_ops::linalg_cond_out::call(self, p, out); +} + +// aten::linalg_cond.p_str(Tensor self, str p) -> Tensor +inline at::Tensor linalg_cond(const at::Tensor & self, c10::string_view p) { + return at::_ops::linalg_cond_p_str::call(self, p); +} + +// aten::linalg_cond.p_str_out(Tensor self, str p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, c10::string_view p) { + return at::_ops::linalg_cond_p_str_out::call(self, p, out); +} +// aten::linalg_cond.p_str_out(Tensor self, str p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_outf(const at::Tensor & self, c10::string_view p, at::Tensor & out) { + return at::_ops::linalg_cond_p_str_out::call(self, p, 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_cond_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7aa01b076070a72160575efb15012d02a58e48ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond_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 linalg_cond { + using schema = 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::linalg_cond"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_cond(Tensor self, Scalar? p=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p); +}; + +struct TORCH_API linalg_cond_out { + using schema = 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::linalg_cond"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_cond.out(Tensor self, Scalar? p=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::Tensor & out); +}; + +struct TORCH_API linalg_cond_p_str { + using schema = at::Tensor (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_cond"; + static constexpr const char* overload_name = "p_str"; + static constexpr const char* schema_str = "linalg_cond.p_str(Tensor self, str p) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::string_view p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view p); +}; + +struct TORCH_API linalg_cond_p_str_out { + using schema = at::Tensor & (const at::Tensor &, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_cond"; + static constexpr const char* overload_name = "p_str_out"; + static constexpr const char* schema_str = "linalg_cond.p_str_out(Tensor self, str p, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::string_view p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view 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/linalg_det_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_det_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8343ced2032a7ba9c501cc63547995d9f34ff327 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_det_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_det { + 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_det"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_det(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_det_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_det"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_det.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_eig_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eig_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f6b734600aab1cd085735b44a47b071af51657c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eig_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_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 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_eigvalsh.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvalsh.h new file mode 100644 index 0000000000000000000000000000000000000000..dcd3cf44e769df318c45979ba9c0b2850276ac90 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvalsh.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_eigvalsh(Tensor self, str UPLO="L") -> Tensor +inline at::Tensor linalg_eigvalsh(const at::Tensor & self, c10::string_view UPLO="L") { + return at::_ops::linalg_eigvalsh::call(self, UPLO); +} + +// aten::linalg_eigvalsh.out(Tensor self, str UPLO="L", *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_eigvalsh_out(at::Tensor & out, const at::Tensor & self, c10::string_view UPLO="L") { + return at::_ops::linalg_eigvalsh_out::call(self, UPLO, out); +} +// aten::linalg_eigvalsh.out(Tensor self, str UPLO="L", *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_eigvalsh_outf(const at::Tensor & self, c10::string_view UPLO, at::Tensor & out) { + return at::_ops::linalg_eigvalsh_out::call(self, UPLO, 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_householder_product_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_householder_product_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36ca732d25aefccd1d5b69c1fd18d74a1d6285fc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_householder_product_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_householder_product(const at::Tensor & input, const at::Tensor & tau); +TORCH_API at::Tensor & linalg_householder_product_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & tau); +TORCH_API at::Tensor & linalg_householder_product_outf(const at::Tensor & input, const at::Tensor & tau, 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_householder_product_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_householder_product_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a6e571dd249b9358e8dfdab7ccca1e029533123e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_householder_product_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_householder_product(const at::Tensor & input, const at::Tensor & tau); +TORCH_API at::Tensor & linalg_householder_product_out(const at::Tensor & input, const at::Tensor & tau, 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_inv_ex_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aee282cd54f7ae6baba77e4199c3b6acfda7790d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_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_inv_ex_out : public at::meta::structured_linalg_inv_ex { +void impl(const at::Tensor & A, bool check_errors, const at::Tensor & inverse, 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_ldl_factor_ex_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e99c633ef6a83494bd59ee54f9ac467fb67ac71a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_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_ldl_factor_ex(const at::Tensor & self, bool hermitian=false, bool check_errors=false); +TORCH_API ::std::tuple linalg_ldl_factor_ex_out(at::Tensor & LD, at::Tensor & pivots, at::Tensor & info, const at::Tensor & self, bool hermitian=false, bool check_errors=false); +TORCH_API ::std::tuple linalg_ldl_factor_ex_outf(const at::Tensor & self, bool hermitian, bool check_errors, at::Tensor & LD, at::Tensor & pivots, at::Tensor & info); + +} // 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_ldl_factor_ex_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8274b5baac9fe8011a28dfe7e1fdd97d65eccdca --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_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_ldl_factor_ex { + using schema = ::std::tuple (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_ldl_factor_ex"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_ldl_factor_ex(Tensor self, *, bool hermitian=False, bool check_errors=False) -> (Tensor LD, Tensor pivots, Tensor info)"; + static ::std::tuple call(const at::Tensor & self, bool hermitian, bool check_errors); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool hermitian, bool check_errors); +}; + +struct TORCH_API linalg_ldl_factor_ex_out { + using schema = ::std::tuple (const at::Tensor &, bool, 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::linalg_ldl_factor_ex"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_ldl_factor_ex.out(Tensor self, *, bool hermitian=False, bool check_errors=False, Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info)"; + static ::std::tuple call(const at::Tensor & self, bool hermitian, bool check_errors, at::Tensor & LD, at::Tensor & pivots, at::Tensor & info); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool hermitian, bool check_errors, at::Tensor & LD, at::Tensor & pivots, 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_ldl_solve_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cb03cfb1516b620cd711ca5e1ca1794e7b4d5a6d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_solve_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_ldl_solve { + 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::linalg_ldl_solve"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_ldl_solve(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False) -> Tensor"; + static at::Tensor call(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian); +}; + +struct TORCH_API linalg_ldl_solve_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::linalg_ldl_solve"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_ldl_solve.out(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, 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_lstsq_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lstsq_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ac5a589dbf7a8792122a53fef6665928296da4d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lstsq_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 ::std::tuple linalg_lstsq(const at::Tensor & self, const at::Tensor & b, ::std::optional rcond=::std::nullopt, ::std::optional driver=::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/linalg_lstsq_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lstsq_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8eb55b55ad2a1aad2d8f9951d3d82a2f1f0ca83a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lstsq_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_lstsq(const at::Tensor & self, const at::Tensor & b, ::std::optional rcond=::std::nullopt, ::std::optional driver=::std::nullopt); +TORCH_API ::std::tuple linalg_lstsq_out(const at::Tensor & self, const at::Tensor & b, ::std::optional rcond, ::std::optional driver, at::Tensor & solution, at::Tensor & residuals, at::Tensor & rank, at::Tensor & singular_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/linalg_lu_factor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor.h new file mode 100644 index 0000000000000000000000000000000000000000..b4da9e5ded69d529437148db43aa98dbe715fb86 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor.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(Tensor A, *, bool pivot=True) -> (Tensor LU, Tensor pivots) +inline ::std::tuple linalg_lu_factor(const at::Tensor & A, bool pivot=true) { + return at::_ops::linalg_lu_factor::call(A, pivot); +} + +// aten::linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots) +inline ::std::tuple linalg_lu_factor_out(at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A, bool pivot=true) { + return at::_ops::linalg_lu_factor_out::call(A, pivot, LU, pivots); +} +// aten::linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots) +inline ::std::tuple linalg_lu_factor_outf(const at::Tensor & A, bool pivot, at::Tensor & LU, at::Tensor & pivots) { + return at::_ops::linalg_lu_factor_out::call(A, pivot, 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/linalg_lu_factor_ex_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7f2d02366e1856a88d2fea36eb0b3f172121ed4b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_factor_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_lu_factor_ex_out : public at::meta::structured_linalg_lu_factor_ex { +void impl(const at::Tensor & A, bool pivot, bool check_errors, 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_lu_solve.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve.h new file mode 100644 index 0000000000000000000000000000000000000000..031db0cafcc374c7301246c962d70803ea3b7223 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_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::linalg_lu_solve(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False) -> Tensor +inline at::Tensor linalg_lu_solve(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false) { + return at::_ops::linalg_lu_solve::call(LU, pivots, B, left, adjoint); +} + +// aten::linalg_lu_solve.out(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::linalg_lu_solve_out::call(LU, pivots, B, left, adjoint, out); +} +// aten::linalg_lu_solve.out(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::linalg_lu_solve_out::call(LU, pivots, B, left, adjoint, 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_matmul_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matmul_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..990d5397d2b067282e6cacf2c7e5ed05bdf79841 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_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 linalg_matmul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & linalg_matmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & linalg_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/linalg_matrix_exp_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ed4a4ac9dbf7d4509ecf56db0912c59e8ad3e5b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_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 linalg_matrix_exp(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/linalg_matrix_rank_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_rank_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64655a41db0c86d75de7b97fad1a34a25c7b87ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_rank_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor linalg_matrix_rank(const at::Tensor & input, const ::std::optional & atol={}, const ::std::optional & rtol={}, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_out(at::Tensor & out, const at::Tensor & input, const ::std::optional & atol={}, const ::std::optional & rtol={}, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_outf(const at::Tensor & input, const ::std::optional & atol, const ::std::optional & rtol, bool hermitian, at::Tensor & out); +TORCH_API at::Tensor linalg_matrix_rank(const at::Tensor & self, ::std::optional atol, ::std::optional rtol, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_out(at::Tensor & out, const at::Tensor & self, ::std::optional atol, ::std::optional rtol, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_outf(const at::Tensor & self, ::std::optional atol, ::std::optional rtol, bool hermitian, at::Tensor & out); +TORCH_API at::Tensor linalg_matrix_rank(const at::Tensor & self, double tol, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_out(at::Tensor & out, const at::Tensor & self, double tol, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_outf(const at::Tensor & self, double tol, bool hermitian, at::Tensor & out); +TORCH_API at::Tensor linalg_matrix_rank(const at::Tensor & input, const at::Tensor & tol, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & tol, bool hermitian=false); +TORCH_API at::Tensor & linalg_matrix_rank_outf(const at::Tensor & input, const at::Tensor & tol, bool hermitian, 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_slogdet_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_slogdet_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2cf36ce144f3958a84b3bc0d2ce623308f18ae1a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_slogdet_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 linalg_slogdet(const at::Tensor & A); +TORCH_API ::std::tuple linalg_slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, const at::Tensor & A); +TORCH_API ::std::tuple linalg_slogdet_outf(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet); + +} // 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_tensorinv.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_tensorinv.h new file mode 100644 index 0000000000000000000000000000000000000000..78f5ad084202776646a41aa4b8596ac0898f2fec --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_tensorinv.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_tensorinv(Tensor self, int ind=2) -> Tensor +inline at::Tensor linalg_tensorinv(const at::Tensor & self, int64_t ind=2) { + return at::_ops::linalg_tensorinv::call(self, ind); +} + +// aten::linalg_tensorinv.out(Tensor self, int ind=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_tensorinv_out(at::Tensor & out, const at::Tensor & self, int64_t ind=2) { + return at::_ops::linalg_tensorinv_out::call(self, ind, out); +} +// aten::linalg_tensorinv.out(Tensor self, int ind=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_tensorinv_outf(const at::Tensor & self, int64_t ind, at::Tensor & out) { + return at::_ops::linalg_tensorinv_out::call(self, ind, 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_tensorinv_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_tensorinv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1cf4c32cb626d7515150d905f5341698c05350d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_tensorinv_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_tensorinv { + 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::linalg_tensorinv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_tensorinv(Tensor self, int ind=2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t ind); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t ind); +}; + +struct TORCH_API linalg_tensorinv_out { + using schema = 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_tensorinv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_tensorinv.out(Tensor self, int ind=2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t ind, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t ind, 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_tensorsolve_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_tensorsolve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2900e8a4b28d00372c9596e04f43604aa47bd4c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_tensorsolve_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_tensorsolve { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::OptionalIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_tensorsolve"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_tensorsolve(Tensor self, Tensor other, int[]? dims=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims); +}; + +struct TORCH_API linalg_tensorsolve_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_tensorsolve"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_tensorsolve.out(Tensor self, Tensor other, int[]? dims=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef 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/linalg_vecdot_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..79c19cb03d998a82f952fb9cfa9fa5ea81116d25 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vecdot_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_vecdot(const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_out(const at::Tensor & x, const at::Tensor & y, 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/linalg_vector_norm_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vector_norm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..3d9583dfe708f4e0e6e9f93570bd7d1a45d08496 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_vector_norm_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_vector_norm : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Scalar & ord, at::OptionalIntArrayRef dim, bool keepdim, ::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/linspace_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linspace_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..33c2231a43bf579fcc5cd19d0d6b75676c9a3734 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/linspace_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 & linspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps); +TORCH_API at::Tensor & linspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, 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/log10_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log10_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e0cfa5ad2060151bcedf3ec30bedda354fee1977 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log10_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 log10(const at::Tensor & self); +TORCH_API at::Tensor & log10_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log10_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log10_(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/log2_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..87c8a7625f685554999225fd2ceb1797a044aa3d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_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_log2_out : public at::meta::structured_log2 { +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/log2_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8d47653a13a5a536664217e71b1992b2e0c8d041 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log2_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 log2 { + 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::log2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "log2(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 log2_ { + 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::log2_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "log2_(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 log2_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::log2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "log2.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/log_normal_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_normal_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f6056f9f1ed68aa1b1db8cfc74689dbff239bbdb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_normal_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 & log_normal_(at::Tensor & self, double mean=1, double std=2, ::std::optional generator=::std::nullopt); + +} // 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/log_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8c58863c391f6d0d5b185315fcab261be750b7b0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_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 log { + 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::log"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "log(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 log_ { + 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::log_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "log_(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 log_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::log"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "log.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/log_sigmoid_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3e0b6d71633c3a1a3e0cb18f7b62dba99e4958db --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_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 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 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_sigmoid_forward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..5905bd9c7832cd8fe0f8e91df978be251417ec19 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_forward.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::log_sigmoid_forward.output(Tensor self, *, Tensor(a!) output, Tensor(b!) buffer) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple log_sigmoid_forward_out(at::Tensor & output, at::Tensor & buffer, const at::Tensor & self) { + return at::_ops::log_sigmoid_forward_output::call(self, output, buffer); +} +// aten::log_sigmoid_forward.output(Tensor self, *, Tensor(a!) output, Tensor(b!) buffer) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple log_sigmoid_forward_outf(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer) { + return at::_ops::log_sigmoid_forward_output::call(self, output, buffer); +} + +// aten::log_sigmoid_forward(Tensor self) -> (Tensor output, Tensor buffer) +inline ::std::tuple log_sigmoid_forward(const at::Tensor & self) { + return at::_ops::log_sigmoid_forward::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/log_sigmoid_forward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..736faedccf2b173e7cb3fb97ed9bc1a98c690590 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/log_sigmoid_forward_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 log_sigmoid_forward_cpu(const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_out_cpu(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer); +TORCH_API ::std::tuple log_sigmoid_forward_cuda(const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_out_cuda(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer); +} // 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/logaddexp_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..644b6296b9828b85f8a80aca4f59ff31a3e5ce92 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_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 logaddexp(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/logaddexp_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5a7d978f97f5397a6ee33f519beb54338a052c3b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_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 logaddexp(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp_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/logaddexp_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cd23c15efbfcd8a1139fd4c2636cb85f7ee040fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_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_logaddexp : 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/logical_and.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and.h new file mode 100644 index 0000000000000000000000000000000000000000..50838ba670f04a9f7ca6dd1c27556103f6b9befc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_and.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::logical_and(Tensor self, Tensor other) -> Tensor +inline at::Tensor logical_and(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logical_and::call(self, other); +} + +// aten::logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logical_and_out::call(self, other, out); +} +// aten::logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::logical_and_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/logical_not.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_not.h new file mode 100644 index 0000000000000000000000000000000000000000..aa722579d254d847fdee02d48021944aa111d3e2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logical_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::logical_not(Tensor self) -> Tensor +inline at::Tensor logical_not(const at::Tensor & self) { + return at::_ops::logical_not::call(self); +} + +// aten::logical_not.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_not_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::logical_not_out::call(self, out); +} +// aten::logical_not.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_not_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::logical_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/logit.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit.h new file mode 100644 index 0000000000000000000000000000000000000000..ddfbc28aeaf46d2c4e90278a3633129a152951e0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit.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::logit(Tensor self, float? eps=None) -> Tensor +inline at::Tensor logit(const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit::call(self, eps); +} + +// aten::logit_(Tensor(a!) self, float? eps=None) -> Tensor(a!) +inline at::Tensor & logit_(at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit_::call(self, eps); +} + +// aten::logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logit_out(at::Tensor & out, const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit_out::call(self, eps, out); +} +// aten::logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logit_outf(const at::Tensor & self, ::std::optional eps, at::Tensor & out) { + return at::_ops::logit_out::call(self, eps, 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/logit_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..fe74b823139613984b5edeb8c22d93e2c1787307 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logit_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::logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & logit_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit_backward_grad_input::call(grad_output, self, eps, grad_input); +} +// aten::logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & logit_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps, at::Tensor & grad_input) { + return at::_ops::logit_backward_grad_input::call(grad_output, self, eps, grad_input); +} + +// aten::logit_backward(Tensor grad_output, Tensor self, float? eps=None) -> Tensor +inline at::Tensor logit_backward(const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::logit_backward::call(grad_output, self, eps); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5fb8ea827cb6d1dbf19c974a7190fad87c7ef6dc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_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 logspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & logspace_out(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out); +TORCH_API at::Tensor & logspace_cuda_out(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out); +TORCH_API at::Tensor logspace(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base=10.0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & logspace_out(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base, at::Tensor & out); +TORCH_API at::Tensor logspace(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base=10.0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & logspace_out(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out); +TORCH_API at::Tensor logspace(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base=10.0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & logspace_out(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base, 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/lshift_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lshift_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64341097b2f76cff8642593915f2ae54f4fa1464 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lshift_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 __lshift__(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & __ilshift__(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor __lshift__(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & __ilshift__(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/lstm_cell.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..f875c9ef4d6b6e1357be37a44eb5d2b7469d327f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_cell.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::lstm_cell(Tensor input, Tensor[] hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> (Tensor, Tensor) +inline ::std::tuple lstm_cell(const at::Tensor & input, at::TensorList hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_hh={}) { + return at::_ops::lstm_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lt.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lt.h new file mode 100644 index 0000000000000000000000000000000000000000..72f6a356b876f277cddaf570ba771d42328c8c5d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lt.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::lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::lt_Scalar_out::call(self, other, out); +} +// aten::lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::lt_Scalar_out::call(self, other, out); +} + +// aten::lt.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor lt(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::lt_Scalar::call(self, other); +} + +// aten::lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::lt_Tensor_out::call(self, other, out); +} +// aten::lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::lt_Tensor_out::call(self, other, out); +} + +// aten::lt.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor lt(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::lt_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/lt_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lt_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..995949a0bf64a77a5c69cb1d25621c2a04d8b60d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lt_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 lt(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & lt_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor lt(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & lt_(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/lu_solve_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f36976b9578f00896a72b5805818e544d40c44b0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_solve_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 lu_solve_out { + using schema = at::Tensor & (const 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::lu_solve"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out); +}; + +struct TORCH_API lu_solve { + using schema = 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::lu_solve"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots); +}; + +}} // 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/lu_unpack_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a27a190d64e4061c2262b4cf054a48ae062f6cd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack_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 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 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/mH_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mH_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fbddffafb1ceda06ffb039c8f91f022c8c54093d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mH_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 mH { + 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::mH"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mH(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/margin_ranking_loss.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/margin_ranking_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..a6c6cebc82ee801b9d87194805db049abe77ebc3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/margin_ranking_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::margin_ranking_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor +inline at::Tensor margin_ranking_loss(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin=0.0, int64_t reduction=at::Reduction::Mean) { + return at::_ops::margin_ranking_loss::call(input1, input2, target, margin, 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/margin_ranking_loss_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/margin_ranking_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..be31eeed6b11e8830fb058b2cd726752838cbc49 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/margin_ranking_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 margin_ranking_loss(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin=0.0, 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/margin_ranking_loss_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/margin_ranking_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dc70e2b03487e1d507a8299df2d2040186634931 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/margin_ranking_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 margin_ranking_loss { + using schema = at::Tensor (const 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::margin_ranking_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "margin_ranking_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input1, const at::Tensor & input2, 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/masked_fill_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d455f2063b9e9d49d5d1064e75b2a9e4482b7714 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_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 & masked_fill_(at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +TORCH_API at::Tensor & masked_fill_(at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); + +} // 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_fill_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..24ce78320b4d1cdf3e3672bcfe833f37115f590f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_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 masked_fill__Scalar { + using schema = at::Tensor & (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::masked_fill_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "masked_fill_.Scalar(Tensor(a!) self, Tensor mask, Scalar value) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +}; + +struct TORCH_API masked_fill_Scalar { + using schema = 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::masked_fill"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "masked_fill.Scalar(Tensor self, Tensor mask, Scalar value) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +}; + +struct TORCH_API masked_fill__Tensor { + using schema = at::Tensor & (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::masked_fill_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "masked_fill_.Tensor(Tensor(a!) self, Tensor mask, Tensor value) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); +}; + +struct TORCH_API masked_fill_Tensor { + using schema = 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::masked_fill"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); +}; + +struct TORCH_API masked_fill_Scalar_out { + using schema = 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::masked_fill"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out); +}; + +struct TORCH_API masked_fill_Tensor_out { + using schema = at::Tensor & (const 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::masked_fill"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & 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/masked_scatter_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7812e5ac74f4471e6a0b37e61954a7b2218ad7ad --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_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_scatter_(at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); + +} // 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_scatter_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ae4925a5b2e3df7066996523333d3b0f6a7b8f2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_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 & masked_scatter_(at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); + +} // 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_select.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select.h new file mode 100644 index 0000000000000000000000000000000000000000..140edab3d8aa7177d64d641d8276322bc5499141 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select.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::masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & masked_select_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask) { + return at::_ops::masked_select_out::call(self, mask, out); +} +// aten::masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & masked_select_outf(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out) { + return at::_ops::masked_select_out::call(self, mask, out); +} + +// aten::masked_select(Tensor self, Tensor mask) -> Tensor +inline at::Tensor masked_select(const at::Tensor & self, const at::Tensor & mask) { + return at::_ops::masked_select::call(self, mask); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_select_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e55beb4712cd80b9d49d7f8b8a80b4dfc597ed80 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_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 masked_select_backward(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & 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/masked_select_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ef5cf7f8011dad41c720a6c7c16bcfa1a0199bd0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_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 masked_select(const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & masked_select_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & masked_select_outf(const at::Tensor & self, const at::Tensor & mask, 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/masked_select_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..85706ff985623e30aed21ed5ff16b7c1497af2b2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_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_select_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::masked_select"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); +}; + +struct TORCH_API masked_select { + 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::masked_select"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "masked_select(Tensor self, Tensor mask) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mask); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask); +}; + +}} // 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_pool1d_with_indices_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool1d_with_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8419b5f0b7ec19f7023c4da9b96e8d76ad4b71c0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool1d_with_indices_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 max_pool1d_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); +} // 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_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..bc583ee265287f0487c2152bba1f3ce5a6f16175 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_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::max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::max_pool2d_backward::call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::max_pool2d_backward.out(Tensor grad_output, 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(a!) +inline at::Tensor & max_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::max_pool2d_backward_out::call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::max_pool2d_backward.out(Tensor grad_output, 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(a!) +inline at::Tensor & max_pool2d_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, at::Tensor & out) { + return at::_ops::max_pool2d_backward_out::call(grad_output, self, 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/max_pool2d_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8bd20d4be40130f5e056e41e48cfff82bf553fad --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_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 & max_pool2d_backward_out(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, 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/max_pool2d_with_indices_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..058f4aed065314d70be2917010811243905e4259 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_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_out_cpu : public at::meta::structured_max_pool2d_with_indices { +void impl(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & out, const at::Tensor & indices); +}; +struct TORCH_API structured_max_pool2d_with_indices_out_cuda : public at::meta::structured_max_pool2d_with_indices { +void impl(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & out, const 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/max_pool3d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6529b769b53c45105c87885475c24bcbcc370245 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_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 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/max_pool3d_with_indices.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_with_indices.h new file mode 100644 index 0000000000000000000000000000000000000000..884fba9020e44849f06a5a8402873efd6a269a7f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_with_indices.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_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::max_pool3d_with_indices_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); +} +// aten::max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::max_pool3d_with_indices_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); +} + +// aten::max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) +inline ::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) { + return at::_ops::max_pool3d_with_indices::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9c24b90fded7f7730f05d6ee4362bd742d320617 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d_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_pool3d_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_pool3d_with_indices"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] 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_pool3d_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_pool3d_with_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] 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/maximum_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82d12c03213d68e17f1a77d7cc03d44cf663da73 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_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_maximum_out : public at::meta::structured_maximum { +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/mean_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8934886e55161f5b61791e86cabb1d24b281d5a0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mean_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 mean(const at::Tensor & self, at::OptionalIntArrayRef 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/median_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/median_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..25b573b1ea3eff55d433d750df2d413ebdfb7a92 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/median_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 & median_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & median_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API ::std::tuple median(const at::Tensor & self, int64_t dim, bool keepdim=false); + +} // 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/min.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min.h new file mode 100644 index 0000000000000000000000000000000000000000..1626e0f097b38a9974f9822b2a516436dab3aea7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min.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::min.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple min(const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::min_dim::call(self, dim, keepdim); +} + +// aten::min.dim_min(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) min, Tensor(b!) min_indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple min_out(at::Tensor & min, at::Tensor & min_indices, const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::min_dim_min::call(self, dim, keepdim, min, min_indices); +} +// aten::min.dim_min(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) min, Tensor(b!) min_indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple min_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices) { + return at::_ops::min_dim_min::call(self, dim, keepdim, min, min_indices); +} + +// aten::min.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple min(const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::min_names_dim::call(self, dim, keepdim); +} + +// aten::min.names_dim_min(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) min, Tensor(b!) min_indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple min_out(at::Tensor & min, at::Tensor & min_indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::min_names_dim_min::call(self, dim, keepdim, min, min_indices); +} +// aten::min.names_dim_min(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) min, Tensor(b!) min_indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple min_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices) { + return at::_ops::min_names_dim_min::call(self, dim, keepdim, min, min_indices); +} + +// aten::min(Tensor self) -> Tensor +inline at::Tensor min(const at::Tensor & self) { + return at::_ops::min::call(self); +} + +// aten::min.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & min_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::min_unary_out::call(self, out); +} +// aten::min.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & min_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::min_unary_out::call(self, out); +} + +// aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & min_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::min_out::call(self, other, out); +} +// aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & min_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::min_out::call(self, other, out); +} + +// aten::min.other(Tensor self, Tensor other) -> Tensor +inline at::Tensor min(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::min_other::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/min_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0107d53a8c51507abd0d4b32002d8dffe19b242a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/min_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_min_dim : 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, 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/minimum.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/minimum.h new file mode 100644 index 0000000000000000000000000000000000000000..6e13e358efd39c03871dd83eb2275ad5c053ca4b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/minimum.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::minimum(Tensor self, Tensor other) -> Tensor +inline at::Tensor minimum(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::minimum::call(self, other); +} + +// aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & minimum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::minimum_out::call(self, other, out); +} +// aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & minimum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::minimum_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/miopen_batch_norm_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_batch_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e0a14023f3b782b652872fc2867ed13c79d7587f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_batch_norm_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 ::std::tuple miopen_batch_norm_backward_out(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); +TORCH_API ::std::tuple miopen_batch_norm_backward(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); +} // 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..f97b72398c55d1bd23b42af6da2db4a89bb39014 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_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::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline 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) { + return at::_ops::miopen_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); +} +namespace symint { + template >> + 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) { + return at::_ops::miopen_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); + } +} + +// aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline 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) { + return at::_ops::miopen_convolution::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_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, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); + } +} + +// aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_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, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_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, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_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, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_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, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_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, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_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, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_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, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_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, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, 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/miopen_convolution_add_relu.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..bb38b46be0e71c6681887a5a57342c0e348cf7c5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu.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::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline 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) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + 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) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor miopen_convolution_add_relu_symint(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + 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, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, 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/miopen_convolution_add_relu_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..30929635220a6a6f31ffd8693214f3071299c10d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_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 miopen_convolution_add_relu { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, 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::miopen_convolution_add_relu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef 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/miopen_convolution_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aa3d7e2b5e2692f011ec14ba05b7ef29e1dc30b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_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_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_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_convolution_transpose.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..0c86a51384622a3da3afd75cbae54291e89565fd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_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::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); + } +} + +// aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, 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/miopen_convolution_transpose_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bcb6922d76cfcdfffa50112f8ee81e8cd3cb3896 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_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 miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_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/mish_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..dda09adcc7bad582fc6d8ceb414542bfd42d2f72 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_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::mish_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor mish_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::mish_backward::call(grad_output, 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/mish_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..be11c29134af79cafd808266d908673db8d7ed4a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mish_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_mish : 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/mkldnn_adaptive_avg_pool2d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..58750e047dca38dd5f9e49bd9b8c7e5f8cc22225 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_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_adaptive_avg_pool2d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor & mkldnn_adaptive_avg_pool2d_out(const at::Tensor & self, at::IntArrayRef output_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/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..43692a36a86148e10995afc829081f92b77daf17 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_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 mkldnn_linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); +TORCH_API ::std::tuple mkldnn_linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, 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/mkldnn_linear_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8ea87e99aab7de64f265d51c9e89ed45c0eb0424 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_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 ::std::tuple mkldnn_linear_backward_out(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple mkldnn_linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::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/mkldnn_linear_backward_weights_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..03c3edd97883cd006e056170086004cd92f4e6d0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_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_linear_backward_weights { + using schema = ::std::tuple (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::mkldnn_linear_backward_weights"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); +}; + +struct TORCH_API mkldnn_linear_backward_weights_out { + using schema = ::std::tuple (const at::Tensor &, 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::mkldnn_linear_backward_weights"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, 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/mkldnn_linear_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70703049873b969a065f99357038b97fa20e2833 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_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 & mkldnn_linear_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias={}); +TORCH_API at::Tensor & mkldnn_linear_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, 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/mkldnn_linear_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..830f05a33c6b9f2e85f1a6e4949e6bd6ef6ce0de --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_linear_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_linear { + using schema = 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::mkldnn_linear"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias); +}; + +struct TORCH_API mkldnn_linear_out { + using schema = 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::mkldnn_linear"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, 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_max_pool2d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63ae3c6a89bda783e0c0ce1635e08b084e98e5a9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_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 mkldnn_max_pool2d { + using schema = 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_pool2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, 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 & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool2d_out { + using schema = 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_pool2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_max_pool2d.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(a!)"; + static at::Tensor & call(const at::Tensor & self, 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 & self, 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/mkldnn_reorder_conv3d_weight_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5e10f311c4b101e842e990eae80eb89bdb0b917d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_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_reorder_conv3d_weight_out_symint(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); +TORCH_API at::Tensor mkldnn_reorder_conv3d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_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/mkldnn_reorder_conv3d_weight_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..490b4aebe5d36301afc8dee8c139ba764e691b6a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_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_reorder_conv3d_weight { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_reorder_conv3d_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_reorder_conv3d_weight(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); +}; + +struct TORCH_API mkldnn_reorder_conv3d_weight_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_reorder_conv3d_weight"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_reorder_conv3d_weight.out(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_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/mkldnn_rnn_layer_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7effedfa59ce8f261d665cb7c7668a8db8de05d9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_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_rnn_layer { + 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 &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_rnn_layer"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +}; + +struct TORCH_API mkldnn_rnn_layer_out { + 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 &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, 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::mkldnn_rnn_layer"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & 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/mm_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4ce90f439875bdd0d81665b2e944603b477b077 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mm_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 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); + +} // 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/mode_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1a47cb43a92765af5e404736dd0ef3b1fd07c41a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mode_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 mode { + 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::mode"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mode(Tensor self, int dim=-1, 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 mode_values { + 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::mode"; + static constexpr const char* overload_name = "values"; + static constexpr const char* schema_str = "mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +}; + +struct TORCH_API mode_dimname { + 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::mode"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "mode.dimname(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 mode_dimname_out { + 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::mode"; + static constexpr const char* overload_name = "dimname_out"; + static constexpr const char* schema_str = "mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +}; + +}} // 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/movedim_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/movedim_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2aa4cec02bfbde390c98ca27eac256c5bb5dfc4d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/movedim_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 movedim(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +TORCH_API at::Tensor movedim(const at::Tensor & self, int64_t source, int64_t destination); + +} // 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/mse_loss.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..6b8a5ccdaca5f653aafc446384d4b670c9aa1249 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_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::mse_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::mse_loss_out::call(self, target, reduction, out); +} +// aten::mse_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out) { + return at::_ops::mse_loss_out::call(self, target, reduction, out); +} + +// aten::mse_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor +inline at::Tensor mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::mse_loss::call(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/mse_loss_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..836dd16d8f57ef8b5a78f98826a5bc0264eb69d0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/mse_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::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::mse_loss_backward_grad_input::call(grad_output, self, target, reduction, grad_input); +} +// aten::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::mse_loss_backward_grad_input::call(grad_output, self, target, reduction, grad_input); +} + +// aten::mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor +inline at::Tensor mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::mse_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/multi_margin_loss_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..91cf225143af27034a4347b4a47e9d7b564580f4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_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 at::Tensor multi_margin_loss_cpu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cpu_backward_out(const at::Tensor & grad_output, 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 & grad_input); +TORCH_API at::Tensor multi_margin_loss_cuda_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cuda_backward_out(const at::Tensor & grad_output, 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 & 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/multi_margin_loss_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a600ab57c880e21d5fd5fed42b20fc7c6d672bdc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/multi_margin_loss_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 multi_margin_loss_backward_grad_input { + using schema = at::Tensor & (const 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_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, 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 & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, 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 & grad_input); +}; + +struct TORCH_API multi_margin_loss_backward { + using schema = at::Tensor (const 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_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, 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 & grad_output, 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/nan_to_num.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num.h new file mode 100644 index 0000000000000000000000000000000000000000..2287e7b576b9a27649e7a2f514048be209ccdfdf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num.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::nan_to_num(Tensor self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor +inline at::Tensor nan_to_num(const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt) { + return at::_ops::nan_to_num::call(self, nan, posinf, neginf); +} + +// aten::nan_to_num_(Tensor(a!) self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor(a!) +inline at::Tensor & nan_to_num_(at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt) { + return at::_ops::nan_to_num_::call(self, nan, posinf, neginf); +} + +// aten::nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nan_to_num_out(at::Tensor & out, const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt) { + return at::_ops::nan_to_num_out::call(self, nan, posinf, neginf, out); +} +// aten::nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nan_to_num_outf(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out) { + return at::_ops::nan_to_num_out::call(self, nan, posinf, neginf, 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/nan_to_num_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5bfc74f721f87cbb270f280e1f830c6a958e0266 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num_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 nan_to_num { + using schema = 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::nan_to_num"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nan_to_num(Tensor self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); +}; + +struct TORCH_API nan_to_num_ { + using schema = at::Tensor & (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::nan_to_num_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nan_to_num_(Tensor(a!) self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); +}; + +struct TORCH_API nan_to_num_out { + using schema = at::Tensor & (const at::Tensor &, ::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::nan_to_num"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..5c59ecc7e50e042c1f74c91d3254d57f41dd3956 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_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::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) +inline ::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) { + return at::_ops::native_batch_norm::call(input, weight, bias, running_mean, running_var, training, momentum, eps); +} + +// aten::native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::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) { + return at::_ops::native_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, momentum, eps, out, save_mean, save_invstd); +} +// aten::native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::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) { + return at::_ops::native_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, momentum, eps, out, save_mean, save_invstd); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..b1c68ac0dd67fd664193dc12977f67959ed9ea33 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_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::native_batch_norm_backward(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::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) { + return at::_ops::native_batch_norm_backward::call(grad_out, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps, output_mask); +} + +// aten::native_batch_norm_backward.out(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_batch_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, 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) { + return at::_ops::native_batch_norm_backward_out::call(grad_out, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps, output_mask, out0, out1, out2); +} +// aten::native_batch_norm_backward.out(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_batch_norm_backward_outf(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, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_batch_norm_backward_out::call(grad_out, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps, output_mask, 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/native_batch_norm_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02cfd1137e238fd13e8118da59486fbb7d3d1e88 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_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_batch_norm_backward_out(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, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple batch_norm_backward_cpu(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); +TORCH_API ::std::tuple batch_norm_backward_cuda(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); +TORCH_API ::std::tuple mkldnn_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 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_dropout_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..93785736cc7facb8c9d46cc378cabc776cf38dbc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_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 native_dropout_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, double p, ::std::optional train); +TORCH_API ::std::tuple native_dropout_outf(const at::Tensor & input, double p, ::std::optional train, 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/native_dropout_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c1513f7cf38ed277b5e1ca9695f19137df99616 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_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 native_dropout(const at::Tensor & input, double p, ::std::optional train); + +} // 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_group_norm_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ea1f66d130a66bf1b9b1107efcc7eeef301e98ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_group_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_group_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymInt, c10::SymInt, c10::SymInt, int64_t, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_group_norm_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_group_norm_backward(Tensor grad_out, Tensor input, Tensor mean, Tensor rstd, Tensor? weight, SymInt N, SymInt C, SymInt HxW, int group, bool[3] output_mask) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::std::array output_mask); +}; + +struct TORCH_API native_group_norm_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymInt, c10::SymInt, c10::SymInt, int64_t, ::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_group_norm_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_group_norm_backward.out(Tensor grad_out, Tensor input, Tensor mean, Tensor rstd, Tensor? weight, SymInt N, SymInt C, SymInt HxW, int group, 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, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::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, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::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_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d43578469947f940a70994fbe0e43a0403af1d0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_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 ::std::tuple native_layer_norm_backward(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 native_layer_norm_backward_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); + +} // 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_norm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..eb877e6c0fa94a7fa9e66a45ec67c2ef15a66332 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/native_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 native_norm { + 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::native_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_norm(Tensor self, Scalar p=2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p); +}; + +struct TORCH_API native_norm_ScalarOpt_dim_dtype { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, at::IntArrayRef, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_norm"; + static constexpr const char* overload_name = "ScalarOpt_dim_dtype"; + static constexpr const char* schema_str = "native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API native_norm_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::native_norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, at::Tensor & out); +}; + +struct TORCH_API native_norm_ScalarOpt_dim_dtype_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, at::IntArrayRef, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_norm"; + static constexpr const char* overload_name = "ScalarOpt_dim_dtype_out"; + static constexpr const char* schema_str = "native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef 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/neg_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9cd2605a26581b8d38ecc9bfb714681eae716a7b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_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 neg(const at::Tensor & self); +TORCH_API at::Tensor & neg_(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/neg_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..abd292c6c04e11f4b362f82bc3dadfe144e9af98 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/neg_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 neg(const at::Tensor & self); +TORCH_API at::Tensor & neg_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & neg_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & neg_(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/new_empty_strided_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_empty_strided_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8ce92337690be2186bbc23a2ef365c81f45b5496 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_empty_strided_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 new_empty_strided { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, 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::new_empty_strided"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "new_empty_strided(Tensor self, SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API new_empty_strided_out { + using schema = at::Tensor & (const at::Tensor &, 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::new_empty_strided"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, 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/new_ones_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_ones_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..75d558f746184d38727dfd7d9b9305adcfdd722a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/new_ones_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 new_ones { + using schema = at::Tensor (const 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::new_ones"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "new_ones(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API new_ones_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::new_ones"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef 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/nextafter.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter.h new file mode 100644 index 0000000000000000000000000000000000000000..c02a7c962d1254c12a7d712950ffa80577616310 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter.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::nextafter.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nextafter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::nextafter_out::call(self, other, out); +} +// aten::nextafter.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nextafter_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::nextafter_out::call(self, other, out); +} + +// aten::nextafter(Tensor self, Tensor other) -> Tensor +inline at::Tensor nextafter(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::nextafter::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/nextafter_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0ec9840ec1fec78758b21232e9d451298ba973e9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_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 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 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_loss2d_forward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..c3a67ed3db9bb8604ca0a57cbdcc09f7ffffdcfc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward.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::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); +} +namespace symint { + template >> + ::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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); + } +} + +// aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); +} +namespace symint { + template >> + ::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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); + } +} + +// aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); +} +namespace symint { + template >> + ::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, c10::SymInt ignore_index) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); + } +} + +// aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); +} +namespace symint { + template >> + ::std::tuple nll_loss2d_forward_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) { + return at::_ops::nll_loss2d_forward_output::call(self, target, weight, reduction, ignore_index, output, total_weight); + } +} + +// aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) +inline ::std::tuple nll_loss2d_forward(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index) { + return at::_ops::nll_loss2d_forward::call(self, target, weight, reduction, ignore_index); +} +namespace symint { + template >> + ::std::tuple nll_loss2d_forward(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index) { + return at::_ops::nll_loss2d_forward::call(self, target, weight, reduction, ignore_index); + } +} + +// aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) +inline ::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) { + return at::_ops::nll_loss2d_forward::call(self, target, weight, reduction, ignore_index); +} +namespace symint { + template >> + ::std::tuple nll_loss2d_forward(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index) { + return at::_ops::nll_loss2d_forward::call(self, target, weight, reduction, ignore_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/nll_loss_forward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2f8981001584094170e9f10dc19444e13de9f3d7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_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_loss_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_loss_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_loss_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_loss_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_loss_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_loss_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_forward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d3900e0b2a9d4b5c427600dc82826353c00bc90c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_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 ::std::tuple nll_loss_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_loss_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_loss_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_loss_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_loss_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_loss_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 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/nonzero_numpy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_numpy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1cf5297da1531a52ae708f07d284caab485b0db4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_numpy_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 nonzero_numpy(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/norm_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37097bdebc42259ec526fe6d8395de814558bd3b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_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 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 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/norm_except_dim_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_except_dim_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..490fcef502ee00339675d7846f1f82d724df6d1c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_except_dim_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 norm_except_dim(const at::Tensor & v, int64_t pow=2, 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/norm_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..49647dca1ebec5894cfd975aad59c1114574a328 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_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_norm_ScalarOpt_dim_dtype : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::OptionalScalarRef p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +}; +struct TORCH_API structured_norm_ScalarOpt_dim : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::OptionalScalarRef p, 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/norm_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a14b7ff37f92f1c8d0087c9a2a6b1783cb823fc7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/norm_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 norm_ScalarOpt_dtype { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "ScalarOpt_dtype"; + static constexpr const char* schema_str = "norm.ScalarOpt_dtype(Tensor self, Scalar? p, *, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype); +}; + +struct TORCH_API norm_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::norm"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "norm.Scalar(Tensor self, Scalar p=2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p); +}; + +struct TORCH_API norm_ScalarOpt_dim_dtype { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, at::IntArrayRef, bool, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "ScalarOpt_dim_dtype"; + static constexpr const char* schema_str = "norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +}; + +struct TORCH_API norm_ScalarOpt_dim { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "ScalarOpt_dim"; + static constexpr const char* schema_str = "norm.ScalarOpt_dim(Tensor self, Scalar? p, int[1] dim, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim); +}; + +struct TORCH_API norm_dtype_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, at::IntArrayRef, bool, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "dtype_out"; + static constexpr const char* schema_str = "norm.dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API norm_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "norm.out(Tensor self, Scalar? p, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API norm_names_ScalarOpt_dim_dtype { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, at::DimnameList, bool, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "names_ScalarOpt_dim_dtype"; + static constexpr const char* schema_str = "norm.names_ScalarOpt_dim_dtype(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype); +}; + +struct TORCH_API norm_names_ScalarOpt_dim { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, at::DimnameList, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "names_ScalarOpt_dim"; + static constexpr const char* schema_str = "norm.names_ScalarOpt_dim(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim); +}; + +struct TORCH_API norm_names_dtype_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, at::DimnameList, bool, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "names_dtype_out"; + static constexpr const char* schema_str = "norm.names_dtype_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API norm_names_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, at::DimnameList, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "names_out"; + static constexpr const char* schema_str = "norm.names_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::DimnameList dim, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API norm_ScalarOpt_dtype_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::norm"; + static constexpr const char* overload_name = "ScalarOpt_dtype_out"; + static constexpr const char* schema_str = "norm.ScalarOpt_dtype_out(Tensor self, Scalar? p, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API norm_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::norm"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "norm.Scalar_out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & 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/normal_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2b4a0779b3035315e7379f5196cdcd3da755efa4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_compositeexplicitautograd_dispatch.h @@ -0,0 +1,38 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 normal_functional(const at::Tensor & self, double mean=0, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & self, double mean=0, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & self, double mean, double std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(double mean, double std, at::IntArrayRef size, ::std::optional generator=::std::nullopt, at::TensorOptions options={}); +TORCH_API at::Tensor normal(double mean, double std, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor normal_symint(double mean, double std, c10::SymIntArrayRef size, ::std::optional generator=::std::nullopt, at::TensorOptions options={}); +TORCH_API at::Tensor normal_symint(double mean, double std, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & normal_out(at::Tensor & out, double mean, double std, at::IntArrayRef size, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(double mean, double std, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & normal_symint_out(at::Tensor & out, double mean, double std, c10::SymIntArrayRef size, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_symint_outf(double mean, double std, 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/normal_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..096073f3713831fa19239027e3954f3f7f0cdfe3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/normal_cuda_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 cuda { + +TORCH_API at::Tensor & normal_(at::Tensor & self, double mean=0, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor normal(const at::Tensor & mean, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, double std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(double mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, double mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(double mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator, 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/nuclear_norm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nuclear_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..07a4cb0d01858469def928d82eda0c504681a7d3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/nuclear_norm_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 nuclear_norm(const at::Tensor & self, bool keepdim=false); +TORCH_API at::Tensor & nuclear_norm_out(const at::Tensor & self, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor nuclear_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & nuclear_norm_out(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, 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/numpy_T.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/numpy_T.h new file mode 100644 index 0000000000000000000000000000000000000000..bfa533a0e1d19c7b843ededfd9d025c2270ed404 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/numpy_T.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/numpy_T_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/numpy_T_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a0dedb30de0a10d51886e761e15e5065b11216c9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/numpy_T_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 numpy_T { + 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::numpy_T"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "numpy_T(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/one_hot.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/one_hot.h new file mode 100644 index 0000000000000000000000000000000000000000..e0cf7924b25811090dcd6e14b833ed044f0043aa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/one_hot.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::one_hot(Tensor self, int num_classes=-1) -> Tensor +inline at::Tensor one_hot(const at::Tensor & self, int64_t num_classes=-1) { + return at::_ops::one_hot::call(self, num_classes); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/one_hot_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/one_hot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f8f465e8fc815141da869e09efa09d74dbe25f8e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/one_hot_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 one_hot(const at::Tensor & self, int64_t num_classes=-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/ones_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1f5e2ce19ebdbece2515bf433816ebb3299f5671 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ones_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 ones_names { + using schema = at::Tensor (at::IntArrayRef, ::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::ones"; + static constexpr const char* overload_name = "names"; + static constexpr const char* schema_str = "ones.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API ones { + 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::ones"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ones(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 ones_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::ones"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "ones.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 ones_names_out { + using schema = at::Tensor & (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::ones"; + static constexpr const char* overload_name = "names_out"; + static constexpr const char* schema_str = "ones.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::IntArrayRef size, ::std::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, ::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/orgqr_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/orgqr_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..67c72028165684a002ce231f269476b0fa98c1f5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/orgqr_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 orgqr(const at::Tensor & self, const at::Tensor & input2); +TORCH_API at::Tensor & orgqr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & input2); +TORCH_API at::Tensor & orgqr_outf(const at::Tensor & self, const at::Tensor & input2, 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/ormqr_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a607185fe9695c9765f0298cbd9d343863e745f7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr_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 ormqr(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false); +TORCH_API at::Tensor & ormqr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false); +TORCH_API at::Tensor & ormqr_outf(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, 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/ormqr_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..721199f4e511799ed3a646c10bce2703938a4d2b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr_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 ormqr(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false); +TORCH_API at::Tensor & ormqr_out(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, 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/ormqr_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4899fc120a4aee50f535e42e00d1a87ebc0cdddf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr_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 ormqr_out { + using schema = at::Tensor & (const 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::ormqr"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "ormqr.out(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, at::Tensor & out); +}; + +struct TORCH_API ormqr { + using schema = at::Tensor (const 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::ormqr"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ormqr(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose); +}; + +}} // 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/outer.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/outer.h new file mode 100644 index 0000000000000000000000000000000000000000..c6052a2abb9c384acde1c6cdc244a443f08041a4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/outer.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::outer(Tensor self, Tensor vec2) -> Tensor +inline at::Tensor outer(const at::Tensor & self, const at::Tensor & vec2) { + return at::_ops::outer::call(self, vec2); +} + +// aten::outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & outer_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2) { + return at::_ops::outer_out::call(self, vec2, out); +} +// aten::outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & outer_outf(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) { + return at::_ops::outer_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/outer_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/outer_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97e904db56d7666cce6f2231ef938b8dbf3cc231 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/outer_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 outer(const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & outer_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & outer_outf(const at::Tensor & self, const at::Tensor & vec2, 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/pad_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1f94db0d5468c2acbf7b11cebe184c2c789de5fa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pad_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 { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::string_view, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::pad"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "pad(Tensor self, SymInt[] pad, str mode=\"constant\", float? value=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef pad, c10::string_view mode, ::std::optional value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, c10::string_view mode, ::std::optional 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/pinverse.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pinverse.h new file mode 100644 index 0000000000000000000000000000000000000000..943bc5a0896a4d3527928fc6befaf8ac257dd37f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pinverse.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::pinverse(Tensor self, float rcond=1e-15) -> Tensor +inline at::Tensor pinverse(const at::Tensor & self, double rcond=1e-15) { + return at::_ops::pinverse::call(self, rcond); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pinverse_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pinverse_native.h new file mode 100644 index 0000000000000000000000000000000000000000..68b1d8f610fbb2be059576db7cf2e3922f98cb40 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pinverse_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 pinverse(const at::Tensor & self, double rcond=1e-15); +} // 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/pixel_unshuffle_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a9d739a33ff9ed3df49ebb9b424f1612a6d23fa5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_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 pixel_unshuffle { + 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::pixel_unshuffle"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "pixel_unshuffle(Tensor self, int downscale_factor) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t downscale_factor); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t downscale_factor); +}; + +struct TORCH_API pixel_unshuffle_out { + using schema = 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::pixel_unshuffle"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "pixel_unshuffle.out(Tensor self, int downscale_factor, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t downscale_factor, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t downscale_factor, 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/poisson_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..43688cfd514695487e22f0715515053ab47dbd44 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/poisson_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 poisson { + 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::poisson"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "poisson(Tensor self, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator); +}; + +struct TORCH_API poisson_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::poisson"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "poisson.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::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/polygamma_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..156c7d40df04f9b4d1fa5dbc6db027605fb43b62 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_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 polygamma_out { + using schema = at::Tensor & (int64_t, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::polygamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "polygamma.out(int n, Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(int64_t n, const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API polygamma { + using schema = 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::polygamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "polygamma(int n, Tensor self) -> Tensor"; + static at::Tensor call(int64_t n, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, const at::Tensor & self); +}; + +struct TORCH_API polygamma_ { + 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::polygamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "polygamma_(Tensor(a!) self, int n) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t n); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, 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/positive_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/positive_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4b9e17b68337cfabfbc7290a20d0b84b1135067f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/positive_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 positive(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/positive_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/positive_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7299086c6be47687f96cff4dffbf69a998d21dd7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/positive_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 positive { + 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::positive"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "positive(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/prelu_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..da5d1c2551572b688dab3f64fca0494922110413 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_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 prelu(const at::Tensor & self, 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/prod_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e7fbbb6b25511cc3204c0a56cb940d0d2619932 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/prod_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 prod(const at::Tensor & self, int64_t dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & prod_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & prod_outf(const at::Tensor & self, int64_t dim, bool keepdim, ::std::optional dtype, 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/promote_types_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/promote_types_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..808f9dec0ce7912dd8ec5560244e10a7d4c042ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/promote_types_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 promote_types { + using schema = at::ScalarType (at::ScalarType, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::promote_types"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "promote_types(ScalarType type1, ScalarType type2) -> ScalarType"; + static at::ScalarType call(at::ScalarType type1, at::ScalarType type2); + static at::ScalarType redispatch(c10::DispatchKeySet dispatchKeySet, at::ScalarType type1, at::ScalarType type2); +}; + +}} // 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_per_channel_scales.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_per_channel_scales.h new file mode 100644 index 0000000000000000000000000000000000000000..2cffe0a88fabc3e25deb082ac0f7c10f9f7890ca --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_per_channel_scales.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::q_per_channel_scales(Tensor self) -> Tensor +inline at::Tensor q_per_channel_scales(const at::Tensor & self) { + return at::_ops::q_per_channel_scales::call(self); +} + +// aten::q_per_channel_scales.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & q_per_channel_scales_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::q_per_channel_scales_out::call(self, out); +} +// aten::q_per_channel_scales.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & q_per_channel_scales_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::q_per_channel_scales_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/q_per_channel_zero_points_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..169021dec8d9f11f7d6f5f152524907781dd7029 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_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 & q_per_channel_zero_points_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & q_per_channel_zero_points_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/q_per_channel_zero_points_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_native.h new file mode 100644 index 0000000000000000000000000000000000000000..019b759bb2d0fcb846731cffad70c56895549814 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_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 & q_per_channel_zero_points_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor q_per_channel_zero_points(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/qr.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qr.h new file mode 100644 index 0000000000000000000000000000000000000000..c671f70ec2f9105ac4c49017fe53cea76e40c8a8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qr.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::qr.Q(Tensor self, bool some=True, *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) +inline ::std::tuple qr_out(at::Tensor & Q, at::Tensor & R, const at::Tensor & self, bool some=true) { + return at::_ops::qr_Q::call(self, some, Q, R); +} +// aten::qr.Q(Tensor self, bool some=True, *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) +inline ::std::tuple qr_outf(const at::Tensor & self, bool some, at::Tensor & Q, at::Tensor & R) { + return at::_ops::qr_Q::call(self, some, Q, R); +} + +// aten::qr(Tensor self, bool some=True) -> (Tensor Q, Tensor R) +inline ::std::tuple qr(const at::Tensor & self, bool some=true) { + return at::_ops::qr::call(self, some); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qr_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qr_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1de67bdc4737e89542c13dcda777f584ba16dfb8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qr_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 qr(const at::Tensor & self, bool some=true); +TORCH_API ::std::tuple qr_out(at::Tensor & Q, at::Tensor & R, const at::Tensor & self, bool some=true); +TORCH_API ::std::tuple qr_outf(const at::Tensor & self, bool some, at::Tensor & Q, at::Tensor & R); + +} // 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/qscheme.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qscheme.h new file mode 100644 index 0000000000000000000000000000000000000000..d8d12e2deb1ef5e8fc38f385e588db70dd12b591 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qscheme.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/qscheme_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qscheme_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9073d800942b82aebe1c5ee8d387b0a91be260c2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/qscheme_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 qscheme { + using schema = at::QScheme (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::qscheme"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "qscheme(Tensor self) -> QScheme"; + static at::QScheme call(const at::Tensor & self); + static at::QScheme 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/quantize_per_tensor_dynamic_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6d37ed92cd430be71dc02b386faed767fe4b100b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_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 quantize_per_tensor_dynamic(const at::Tensor & self, at::ScalarType dtype, bool reduce_range); + +} // 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/quantized_max_pool1d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0e4c3d1c408fc61644015484a03412ef2d74c4a1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d_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_pool1d_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_pool1d(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_relu_cell_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_relu_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4db15157af698069e2259d46536dcdf8c8855b7e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_relu_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 at::Tensor quantized_rnn_relu_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 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/randint.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint.h new file mode 100644 index 0000000000000000000000000000000000000000..6953d7cde3e4b0aa47bebd560cabb9c2a5142f66 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint.h @@ -0,0 +1,383 @@ +#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(SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint(int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint::call(high, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint::call(high, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint(SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randint::call(high, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randint::call(high, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::randint(SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint::call(high, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint::call(high, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint(SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randint::call(high, size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randint::call(high, size, dtype, layout, device, pin_memory); + } +} + +// aten::randint.generator(SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_generator::call(high, c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_generator::call(high, c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint.generator(SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::randint_generator::call(high, c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + 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) { + return at::_ops::randint_generator::call(high, c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); + } +} + +// aten::randint.generator(SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_generator::call(high, size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_generator::call(high, size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint.generator(SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::randint_generator::call(high, size, generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randint_generator::call(high, size, generator, dtype, layout, device, pin_memory); + } +} + +// aten::randint.low(SymInt low, SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low::call(low, high, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low::call(low, high, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint.low(SymInt low, SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::randint_low::call(low, high, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + 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) { + return at::_ops::randint_low::call(low, high, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::randint.low(SymInt low, SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low::call(low, high, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low::call(low, high, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint.low(SymInt low, SymInt high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::randint_low::call(low, high, size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randint_low::call(low, high, size, dtype, layout, device, pin_memory); + } +} + +// aten::randint.low_generator(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low_generator::call(low, high, c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low_generator::call(low, high, c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint.low_generator(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::randint_low_generator::call(low, high, c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + 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) { + return at::_ops::randint_low_generator::call(low, high, c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); + } +} + +// aten::randint.low_generator(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low_generator::call(low, high, size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randint_low_generator::call(low, high, size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randint.low_generator(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::randint_low_generator::call(low, high, size, generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randint(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) { + return at::_ops::randint_low_generator::call(low, high, size, generator, dtype, layout, device, pin_memory); + } +} + +// aten::randint.out(SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size) { + return at::_ops::randint_out::call(high, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size) { + return at::_ops::randint_out::call(high, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::randint.out(SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::randint_out::call(high, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::randint_out::call(high, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::randint.out(SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size) { + return at::_ops::randint_out::call(high, size, out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size) { + return at::_ops::randint_out::call(high, size, out); + } +} + +// aten::randint.out(SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_outf(c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::randint_out::call(high, size, out); +} +namespace symint { + template >> + at::Tensor & randint_outf(c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::randint_out::call(high, size, out); + } +} + +// aten::randint.generator_out(SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::randint_generator_out::call(high, c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::randint_generator_out::call(high, c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::randint.generator_out(SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_generator_out::call(high, c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_generator_out::call(high, c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::randint.generator_out(SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::randint_generator_out::call(high, size, generator, out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::randint_generator_out::call(high, size, generator, out); + } +} + +// aten::randint.generator_out(SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_outf(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_generator_out::call(high, size, generator, out); +} +namespace symint { + template >> + at::Tensor & randint_outf(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_generator_out::call(high, size, generator, out); + } +} + +// aten::randint.low_out(SymInt low, SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size) { + return at::_ops::randint_low_out::call(low, high, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size) { + return at::_ops::randint_low_out::call(low, high, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::randint.low_out(SymInt low, SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::randint_low_out::call(low, high, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::randint_low_out::call(low, high, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::randint.low_out(SymInt low, SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size) { + return at::_ops::randint_low_out::call(low, high, size, out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size) { + return at::_ops::randint_low_out::call(low, high, size, out); + } +} + +// aten::randint.low_out(SymInt low, SymInt high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::randint_low_out::call(low, high, size, out); +} +namespace symint { + template >> + at::Tensor & randint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::randint_low_out::call(low, high, size, out); + } +} + +// aten::randint.low_generator_out(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::randint_low_generator_out::call(low, high, c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::randint_low_generator_out::call(low, high, c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::randint.low_generator_out(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_low_generator_out::call(low, high, c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_low_generator_out::call(low, high, c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::randint.low_generator_out(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::randint_low_generator_out::call(low, high, size, generator, out); +} +namespace symint { + template >> + at::Tensor & randint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::randint_low_generator_out::call(low, high, size, generator, out); + } +} + +// aten::randint.low_generator_out(SymInt low, SymInt high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_symint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_low_generator_out::call(low, high, size, generator, out); +} +namespace symint { + template >> + at::Tensor & randint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randint_low_generator_out::call(low, high, size, 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/randint_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2671c8a76c2a491e85d16944603c90550d036854 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randint_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 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_out(int64_t high, at::IntArrayRef size, at::Tensor & out); +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_out(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +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_out(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out); +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_out(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, 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_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a83acf88ebe2d483406d6a32ec64195c9160ba9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_compositeexplicitautograd_dispatch.h @@ -0,0 +1,51 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 randn(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional generator, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional names); +TORCH_API at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional names); +TORCH_API at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator, ::std::optional names); +TORCH_API at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names); +TORCH_API at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, 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/randn_like_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1539409f603575fd7441632c507fd440111c8cef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/randn_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 randn_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::randn_like"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "randn_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 randn_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::randn_like"; + static constexpr const char* overload_name = "generator"; + static constexpr const char* schema_str = "randn_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 randn_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::randn_like"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "randn_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 randn_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::randn_like"; + static constexpr const char* overload_name = "generator_out"; + static constexpr const char* schema_str = "randn_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/range_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..62d8337758f60872af12a0a1571a39f801bc9b44 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/range_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 range_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::range"; + static constexpr const char* overload_name = "step"; + static constexpr const char* schema_str = "range.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 range { + 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::range"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "range(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 range_out_ { + using schema = 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::range"; + static constexpr const char* overload_name = "out_"; + static constexpr const char* schema_str = "range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & start, const at::Scalar & end, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, at::Tensor & out); +}; + +struct TORCH_API range_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::range"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "range.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/ravel_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00fc93906edc1669ae2d22d2f289afd29bb01a0b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/ravel_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 ravel(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/real_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/real_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb0f37044a0fb25b417c40f7975101691f0b03d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/real_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 real(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/reciprocal_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reciprocal_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e3a22d615eba06045a93e1c8ae94b3b0448e68fd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reciprocal_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_reciprocal : 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/refine_names_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/refine_names_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..95e6abf385e47564314b23cb701f05b39408fdfa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/refine_names_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 refine_names(const at::Tensor & self, 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/reflection_pad1d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bb77b4c04f708ca1d1449d7ec31013d240bf6c61 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_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_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & reflection_pad1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_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_pad1d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0075469982bda8e915ea82aef0cd90dcc0962fb9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_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_reflection_pad1d : 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/reflection_pad1d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aa0c1c5511638309677ed5a4d758aa77907df0ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_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_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & reflection_pad1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_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/reflection_pad1d_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8dcbdcebf6f19b73fb333df05190415ff8b60fc0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_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_reflection_pad1d_out_cpu : public at::meta::structured_reflection_pad1d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +struct TORCH_API structured_reflection_pad1d_out_cuda : public at::meta::structured_reflection_pad1d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +TORCH_API at::Tensor & reflection_pad1d_out_quantized_cpu(const at::Tensor & self, at::IntArrayRef padding, 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/reflection_pad3d_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c2fd9f0d0a960a85eb1bf8094eac525f6ab07780 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_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 reflection_pad3d_backward_grad_input { + using schema = at::Tensor & (const 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_pad3d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); +}; + +struct TORCH_API reflection_pad3d_backward { + using schema = at::Tensor (const 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_pad3d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "reflection_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, 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_pad3d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d271061b6f951acde968cd33b8ed7c72a1b074ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_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(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 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/relu6_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu6_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e8246c7185c24c51a8ea2209dece9f46d0f2a3ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu6_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 relu6 { + 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::relu6"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "relu6(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 relu6_ { + 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::relu6_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "relu6_(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/relu_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..209ec3c91bca50a0af60b690052ea6d2bca4d976 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/relu_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 relu(const at::Tensor & self); +TORCH_API at::Tensor & relu_(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/remainder.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder.h new file mode 100644 index 0000000000000000000000000000000000000000..e0fd17c71ff3600301a9f9e841559fa5d5f06c5a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/remainder.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::remainder.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::remainder_Scalar_out::call(self, other, out); +} +// aten::remainder.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & remainder_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::remainder_Scalar_out::call(self, other, out); +} + +// aten::remainder.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor remainder(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::remainder_Scalar::call(self, other); +} + +// aten::remainder.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::remainder_Tensor_out::call(self, other, out); +} +// aten::remainder.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & remainder_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::remainder_Tensor_out::call(self, other, out); +} + +// aten::remainder.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor remainder(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::remainder_Tensor::call(self, other); +} + +// aten::remainder.Scalar_Tensor(Scalar self, Tensor other) -> Tensor +inline at::Tensor remainder(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::remainder_Scalar_Tensor::call(self, other); +} + +// aten::remainder.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & remainder_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::remainder_Scalar_Tensor_out::call(self, other, out); +} +// aten::remainder.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & remainder_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::remainder_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/rename_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rename_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8f33e5b15d8999003abf5bef5b7ea30ec2feeb30 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rename_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 & rename_(at::Tensor & self, ::std::optional names); +TORCH_API at::Tensor rename(const at::Tensor & self, ::std::optional 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/renorm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/renorm.h new file mode 100644 index 0000000000000000000000000000000000000000..2cf546115591109e1bb7452112ec1990101f6aa7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/renorm.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::renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & renorm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm) { + return at::_ops::renorm_out::call(self, p, dim, maxnorm, out); +} +// aten::renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & renorm_outf(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, at::Tensor & out) { + return at::_ops::renorm_out::call(self, p, dim, maxnorm, out); +} + +// aten::renorm(Tensor self, Scalar p, int dim, Scalar maxnorm) -> Tensor +inline at::Tensor renorm(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm) { + return at::_ops::renorm::call(self, p, dim, maxnorm); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/renorm_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/renorm_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7df68f15bf8c1fac2be645cdbd3dbf43a46016eb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/renorm_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 renorm(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); +TORCH_API at::Tensor & renorm_(at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); + +} // 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/repeat_interleave.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_interleave.h new file mode 100644 index 0000000000000000000000000000000000000000..831ef72bde558941b43392897107e5eac479d0cb --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_interleave.h @@ -0,0 +1,141 @@ +#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::repeat_interleave.Tensor(Tensor repeats, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave(const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor repeat_interleave(const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt); + } +} + +// aten::repeat_interleave.Tensor(Tensor repeats, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave_symint(const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size); +} +namespace symint { + template >> + at::Tensor repeat_interleave(const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size); + } +} + +// aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt); + } +} + +// aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave_symint(const at::Tensor & self, const at::Tensor & repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size); +} +namespace symint { + template >> + at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size); + } +} + +// aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave(const at::Tensor & self, int64_t repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor repeat_interleave(const at::Tensor & self, int64_t repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt); + } +} + +// aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave_symint(const at::Tensor & self, c10::SymInt repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size); +} +namespace symint { + template >> + at::Tensor repeat_interleave(const at::Tensor & self, c10::SymInt repeats, ::std::optional dim=::std::nullopt, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt, out); +} +namespace symint { + template >> + at::Tensor & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt, out); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, ::std::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt, out); +} +namespace symint { + template >> + at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, ::std::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? ::std::make_optional(c10::SymInt(*output_size)) : ::std::nullopt, out); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_symint_out(at::Tensor & out, const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); +} +namespace symint { + template >> + at::Tensor & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, ::std::optional output_size=::std::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_symint_outf(const at::Tensor & repeats, ::std::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); +} +namespace symint { + template >> + at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, ::std::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, 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/replication_pad1d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..8c10e3a02a73c11330efaf7789a97012696e1e5a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_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::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); +} +namespace symint { + template >> + at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); + } +} + +// aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); +} +namespace symint { + template >> + at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); + } +} + +// aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); +} +namespace symint { + template >> + at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); + } +} + +// aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); +} +namespace symint { + template >> + at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); + } +} + +// aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor +inline at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template >> + at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor +inline at::Tensor replication_pad1d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, padding); +} +namespace symint { + template >> + at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, 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_pad1d_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e49293f8224ca07f31f770513ef11bd956f5e8ca --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_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 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); +TORCH_API at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & replication_pad1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, 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/replication_pad1d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c91464dbfee8ed943764a0f2a49c3d591e36d4a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_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 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); +TORCH_API at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & replication_pad1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_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/replication_pad1d_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ddd850e2077636f8f14a949e82991730c964271e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_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_replication_pad1d_backward_out_cpu : public at::meta::structured_replication_pad1d_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::ArrayRef padding, const at::Tensor & grad_input); +}; +struct TORCH_API structured_replication_pad1d_backward_out_cuda : public at::meta::structured_replication_pad1d_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::ArrayRef padding, 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/replication_pad1d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..363ab3bd33c191ecb6c7f858eb45b22c8bffb557 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_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_pad1d : 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_pad2d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..670b5aac71260cf899ce10a1c2eef49ead455b9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_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 replication_pad2d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad2d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, 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/replication_pad3d_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4bac2e7cd5cce6493d8428d9e60606ae16a5c663 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_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 replication_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_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/replication_pad3d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..dff2a0b05590e71c3a95f3684ee2daa8e8fa5704 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_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_pad3d : 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_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..baf8e3d4a68c6d897c218b5bc9c5e227a3275849 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/replication_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 replication_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_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/requires_grad_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/requires_grad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..036f4e8fe1bc85aff3ad5e3e43f03f40023f6db8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/requires_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 at::Tensor & requires_grad_(at::Tensor & self, bool requires_grad=true); +} // 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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d11c132f62754c14486256e3ebf89fc25cfcc35b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_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_symint(const at::Tensor & self, c10::SymIntArrayRef shape); +TORCH_API at::Tensor reshape_nested_symint(const at::Tensor & self, c10::SymIntArrayRef shape); +} // 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.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize.h new file mode 100644 index 0000000000000000000000000000000000000000..da51e5117d796bef3378313ca6c41a14dbcde66d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize.h @@ -0,0 +1,111 @@ +#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 >> + const at::Tensor & resize_(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_::call(self, c10::fromIntArrayRefSlow(size), memory_format); + } +} + +namespace symint { + template >> + const at::Tensor & resize_(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_::call(self, size, memory_format); + } +} + +// aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_out(const at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_out::call(self, c10::fromIntArrayRefSlow(size), memory_format, out); +} +namespace symint { + template >> + const at::Tensor & resize_out(const at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_out::call(self, c10::fromIntArrayRefSlow(size), memory_format, out); + } +} + +// aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_outf(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format, const at::Tensor & out) { + return at::_ops::resize_out::call(self, c10::fromIntArrayRefSlow(size), memory_format, out); +} +namespace symint { + template >> + const at::Tensor & resize_outf(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format, const at::Tensor & out) { + return at::_ops::resize_out::call(self, c10::fromIntArrayRefSlow(size), memory_format, out); + } +} + +// aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_symint_out(const at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_out::call(self, size, memory_format, out); +} +namespace symint { + template >> + const at::Tensor & resize_out(const at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_out::call(self, size, memory_format, out); + } +} + +// aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format, const at::Tensor & out) { + return at::_ops::resize_out::call(self, size, memory_format, out); +} +namespace symint { + template >> + const at::Tensor & resize_outf(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format, const at::Tensor & out) { + return at::_ops::resize_out::call(self, size, memory_format, out); + } +} + +// aten::resize(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor resize(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize::call(self, c10::fromIntArrayRefSlow(size), memory_format); +} +namespace symint { + template >> + at::Tensor resize(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize::call(self, c10::fromIntArrayRefSlow(size), memory_format); + } +} + +// aten::resize(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor resize_symint(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize::call(self, size, memory_format); +} +namespace symint { + template >> + at::Tensor resize(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize::call(self, size, 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/resize_as.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as.h new file mode 100644 index 0000000000000000000000000000000000000000..df38531060cfd7f30f2a8ff4bd253a307e84f63e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as.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::resize_as_(Tensor(a!) self, Tensor the_template, *, MemoryFormat? memory_format=None) -> Tensor(a!) +inline const at::Tensor & resize_as_(const at::Tensor & self, const at::Tensor & the_template, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_as_::call(self, the_template, memory_format); +} + +// aten::resize_as.out(Tensor self, Tensor the_template, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_as_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & the_template, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_as_out::call(self, the_template, memory_format, out); +} +// aten::resize_as.out(Tensor self, Tensor the_template, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_as_outf(const at::Tensor & self, const at::Tensor & the_template, ::std::optional memory_format, const at::Tensor & out) { + return at::_ops::resize_as_out::call(self, the_template, memory_format, out); +} + +// aten::resize_as(Tensor self, Tensor the_template, *, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor resize_as(const at::Tensor & self, const at::Tensor & the_template, ::std::optional memory_format=::std::nullopt) { + return at::_ops::resize_as::call(self, the_template, 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/resize_as_sparse.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse.h new file mode 100644 index 0000000000000000000000000000000000000000..a836822cd54a9382c63e303c51937eed99c1ceaa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse.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::resize_as_sparse_(Tensor(a!) self, Tensor the_template) -> Tensor(a!) +inline const at::Tensor & resize_as_sparse_(const at::Tensor & self, const at::Tensor & the_template) { + return at::_ops::resize_as_sparse_::call(self, the_template); +} + +// aten::resize_as_sparse.out(Tensor self, Tensor the_template, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_as_sparse_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & the_template) { + return at::_ops::resize_as_sparse_out::call(self, the_template, out); +} +// aten::resize_as_sparse.out(Tensor self, Tensor the_template, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & resize_as_sparse_outf(const at::Tensor & self, const at::Tensor & the_template, const at::Tensor & out) { + return at::_ops::resize_as_sparse_out::call(self, the_template, out); +} + +// aten::resize_as_sparse(Tensor self, Tensor the_template) -> Tensor +inline at::Tensor resize_as_sparse(const at::Tensor & self, const at::Tensor & the_template) { + return at::_ops::resize_as_sparse::call(self, the_template); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9e9dabc5e628e795136360bd6c34b7f51a1e3074 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_as_sparse_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 const at::Tensor & resize_as_sparse_(const at::Tensor & self, const at::Tensor & the_template); + +} // 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/resize_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2009d539cbe50e6b6d3c7d9ed45b285e739b8c74 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resize_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 const at::Tensor & resize_(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt); +TORCH_API const at::Tensor & resize__symint(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::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/resolve_conj_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_conj_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e06fb0e940881da036232a76ac5216894f42135d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_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 resolve_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::resolve_conj"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "resolve_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/resolve_neg_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2fd899694eaa31d41257f15874dc1bb210e0e2e9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/resolve_neg_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 resolve_neg(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/result_type_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/result_type_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4d0cc2433367d85723dff487e61ca7f18cf9a4b5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/result_type_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 result_type_Tensor { + using schema = at::ScalarType (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::result_type"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType"; + static at::ScalarType call(const at::Tensor & tensor, const at::Tensor & other); + static at::ScalarType redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & tensor, const at::Tensor & other); +}; + +struct TORCH_API result_type_Scalar { + using schema = at::ScalarType (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::result_type"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType"; + static at::ScalarType call(const at::Tensor & tensor, const at::Scalar & other); + static at::ScalarType redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & tensor, const at::Scalar & other); +}; + +struct TORCH_API result_type_Scalar_Tensor { + using schema = at::ScalarType (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::result_type"; + static constexpr const char* overload_name = "Scalar_Tensor"; + static constexpr const char* schema_str = "result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType"; + static at::ScalarType call(const at::Scalar & scalar, const at::Tensor & tensor); + static at::ScalarType redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & scalar, const at::Tensor & tensor); +}; + +struct TORCH_API result_type_Scalar_Scalar { + using schema = at::ScalarType (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::result_type"; + static constexpr const char* overload_name = "Scalar_Scalar"; + static constexpr const char* schema_str = "result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType"; + static at::ScalarType call(const at::Scalar & scalar1, const at::Scalar & scalar2); + static at::ScalarType redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & scalar1, const at::Scalar & scalar2); +}; + +}} // 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/retains_grad.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/retains_grad.h new file mode 100644 index 0000000000000000000000000000000000000000..8e08306cfa5f9a852aa5ad7278d514a0752680ef --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/retains_grad.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/rms_norm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rms_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d21bd722e0364e7bedb3eaf5195f0fe7fdc0f1bf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rms_norm_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 rms_norm_symint(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight={}, ::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/rnn_relu_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b53c4ecf54bbb41e52684409b16f7fcd5257f870 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_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 rnn_relu_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::rnn_relu"; + static constexpr const char* overload_name = "input"; + static constexpr const char* schema_str = "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)"; + 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 rnn_relu_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::rnn_relu"; + static constexpr const char* overload_name = "data"; + static constexpr const char* schema_str = "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)"; + 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/rnn_tanh_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7db4298d3cb78f1d96a27604ae60881a2e27b7c8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_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 rnn_tanh_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::rnn_tanh"; + static constexpr const char* overload_name = "input"; + static constexpr const char* schema_str = "rnn_tanh.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 rnn_tanh_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::rnn_tanh"; + static constexpr const char* overload_name = "data"; + static constexpr const char* schema_str = "rnn_tanh.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/round_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/round_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ee0d1b77368de0e00e94c12637a46150cd165f64 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/round_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 round(const at::Tensor & self); +TORCH_API at::Tensor & round_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & round_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & round_(at::Tensor & self); +TORCH_API at::Tensor round(const at::Tensor & self, int64_t decimals); +TORCH_API at::Tensor & round_out(at::Tensor & out, const at::Tensor & self, int64_t decimals); +TORCH_API at::Tensor & round_outf(const at::Tensor & self, int64_t decimals, at::Tensor & out); +TORCH_API at::Tensor & round_(at::Tensor & self, int64_t decimals); + +} // 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/round_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/round_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c6950953bec89c6abc90f393281147cc0d9d6175 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/round_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 round { + 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::round"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "round(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 round_ { + 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::round_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "round_(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 round_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::round"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "round.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 round_decimals { + 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::round"; + static constexpr const char* overload_name = "decimals"; + static constexpr const char* schema_str = "round.decimals(Tensor self, *, int decimals) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t decimals); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t decimals); +}; + +struct TORCH_API round__decimals { + 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::round_"; + static constexpr const char* overload_name = "decimals"; + static constexpr const char* schema_str = "round_.decimals(Tensor(a!) self, *, int decimals) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t decimals); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t decimals); +}; + +struct TORCH_API round_decimals_out { + using schema = 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::round"; + static constexpr const char* overload_name = "decimals_out"; + static constexpr const char* schema_str = "round.decimals_out(Tensor self, *, int decimals, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t decimals, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t decimals, 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/rrelu_with_noise_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..559db5ce4b307e633df3992e7494891d71028bb1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_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 ::std::tuple rrelu_with_noise_functional(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::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/rrelu_with_noise_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c10b01f286d8735e5b54747747ead36e2fcd0e08 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise_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 rrelu_with_noise_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &, const at::Scalar &, const at::Scalar &, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rrelu_with_noise"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "rrelu_with_noise.out(Tensor self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API rrelu_with_noise { + using schema = at::Tensor (const at::Tensor &, at::Tensor &, const at::Scalar &, const at::Scalar &, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rrelu_with_noise"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rrelu_with_noise(Tensor self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator); +}; + +struct TORCH_API rrelu_with_noise_ { + using schema = at::Tensor & (at::Tensor &, at::Tensor &, const at::Scalar &, const at::Scalar &, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rrelu_with_noise_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rrelu_with_noise_(Tensor(a!) self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator); +}; + +struct TORCH_API rrelu_with_noise_functional { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::rrelu_with_noise_functional"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "rrelu_with_noise_functional(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> (Tensor, Tensor noise_out)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::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/rshift_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rshift_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..070d7c3a3898755b173127b4a651e1dd3b8d3cb7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rshift_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 & __irshift__(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & __irshift__(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/rsqrt_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7607ec5d508166051ce5d57dcbdc6f79ccd2cb62 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_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 rsqrt(const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rsqrt_(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/rsqrt_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4d175d3c0ec72afe7f598c441ef0b84366697f19 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_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 rsqrt(const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rsqrt_(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/scatter_add_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c23067f02acbb1d831ef27aba02989930371f7ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_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 scatter_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); + +} // 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/scatter_add_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..35bc6918be505c05f768f22deae4761fe8678113 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_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 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 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_add_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..34bd6db8852c639e2b4e6308f787159508fdf79c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_add_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_scatter_add : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +}; + +} // 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/scatter_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f89894ce5c36bdbcea62244dfa6c9714e552569 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +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_(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_(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_(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_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); + +} // 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/scatter_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..473be59a630208ef0d67699bf9e7826ff4858b22 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_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 scatter(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor scatter(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Scalar & value); + +} // 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/scatter_reduce_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_reduce_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c7f6106b53c94fb59ffa2304d5ca1c0ea557f318 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_reduce_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 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_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self=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/select_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c1ff8e6cabc07ea8a7066485792774d390380f19 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_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 & select_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index); +TORCH_API at::Tensor & select_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index, at::Tensor & out); +TORCH_API at::Tensor & select_backward_symint_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index); +TORCH_API at::Tensor & select_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, 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/select_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d8651042603ddebc02a2486e90f443c92634c14c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_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 select(const at::Tensor & self, int64_t dim, int64_t index); +TORCH_API at::Tensor select_symint(const at::Tensor & self, int64_t dim, c10::SymInt index); + +} // 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/select_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37a7008603e8a2150a6baff04289ee8f741006a0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_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 select(const at::Tensor & self, at::Dimname dim, int64_t index); + +} // 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/select_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..2c0252f980e867a357d9abe263e7e62fb2311111 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_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::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor +inline at::Tensor select_copy(const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int::call(self, dim, index); +} +namespace symint { + template >> + at::Tensor select_copy(const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int::call(self, dim, index); + } +} + +// aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor +inline at::Tensor select_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int::call(self, dim, index); +} +namespace symint { + template >> + at::Tensor select_copy(const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int::call(self, dim, index); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_symint_outf(const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, 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/select_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b8c05c3146ef959348462a398b37698556a0845f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_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 select(const at::Tensor & self, at::Dimname dim, int64_t index); +TORCH_API at::Tensor select_symint(const at::Tensor & self, int64_t dim, c10::SymInt index); +TORCH_API at::Tensor select_nested(const at::Tensor & self, int64_t dim, int64_t index); +TORCH_API at::Tensor select_sparse_csr(const at::Tensor & self, int64_t dim, int64_t index); +} // 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/select_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6e1a10e3518ffb7e323b4345f9d072d7e49338b3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_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 select_Dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::select"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "select.Dimname(Tensor(a) self, Dimname dim, int index) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, int64_t index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, int64_t index); +}; + +struct TORCH_API select_int { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::select"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "select.int(Tensor(a) self, int dim, SymInt index) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t dim, c10::SymInt index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt 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/select_scatter_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_scatter_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2d826db67b8f1fe132aa08c9bbcd1234ef7fc90a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/select_scatter_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_scatter(const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index); +TORCH_API at::Tensor select_scatter_symint(const at::Tensor & self, const at::Tensor & src, 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/set_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91a7dca9565b3aca53749a7e06040c56b234ed20 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/set_cuda_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 cuda { + +TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_(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, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_(at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_(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/sigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..564c0c9ea944c0668303daf0a4b1c83461563bc1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_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 sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); + +} // 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/sigmoid_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b208538cff9b20db34ab0d4c19b78bcf2cea4420 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_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 sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_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/sigmoid_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..baabaafb604cadc1c9f1befba97fcea537a300d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/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 sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, 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/sign.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sign.h new file mode 100644 index 0000000000000000000000000000000000000000..1489e89c464b98e3b54c34577669ebd124e2d96b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sign.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::sign(Tensor self) -> Tensor +inline at::Tensor sign(const at::Tensor & self) { + return at::_ops::sign::call(self); +} + +// aten::sign.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sign_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::sign_out::call(self, out); +} +// aten::sign.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sign_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::sign_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/sign_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sign_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..271c08b1a677e76be3962d5b7d8003931179a228 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sign_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_sign : 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/signbit_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..96522e59950bc3205a02fd2d1d24c06e7623959b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_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 signbit(const at::Tensor & self); +TORCH_API at::Tensor & signbit_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & signbit_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/signbit_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..95c4c98010bdd179f34dbcf3d6b8a9f6e8353fd9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_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 signbit(const at::Tensor & self); +TORCH_API at::Tensor & signbit_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & signbit_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/silu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44fcbfbf3a9ab49660c38e119a991685fd373c94 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_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 silu_backward(const at::Tensor & grad_output, 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/silu_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..89a8778cf09132371be8485adae8ffd98f143302 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_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 silu_backward(const at::Tensor & grad_output, 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/silu_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..289a72262271b6297aef2d2eee72764cd9825b0a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_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 silu_backward(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & silu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & silu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, 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/silu_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..1696f650404bf3bfb96ced73385ce6b62d631381 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/silu_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_silu_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/sinc_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3fb45e7b7cf68cd4b082db77d0272172537e9a71 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_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 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 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/sinc_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cff637c82f897ff1dc278d87da4867ea1694bc69 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_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 sinc { + 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::sinc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sinc(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 sinc_ { + 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::sinc_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sinc_(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 sinc_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::sinc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sinc.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/sinh_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..360327d0f822aa3e18c5f036edcd983e84c72661 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_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 sinh(const at::Tensor & self); +TORCH_API at::Tensor & sinh_(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/sinh_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..71ce2a05fe2d5ea3aaf1f5e0097c797c56b49139 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_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 sinh(const at::Tensor & self); +TORCH_API at::Tensor & sinh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_(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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9f99694739d9f619bf60bdf5b2ba9b57a69e7cc6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_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 sinh { + 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::sinh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sinh(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 sinh_ { + 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::sinh_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sinh_(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 sinh_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::sinh"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sinh.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/size_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..edf3567b2d0d8eebc92ca666d5169f8863a48cee --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/size_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 int64_t size(const at::Tensor & self, int64_t dim); +TORCH_API int64_t size(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/slice_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..6e2ed421c858fe1c9c99010e0cc36dcd8e96c0aa --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_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::slice_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step) -> Tensor +inline at::Tensor slice_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t start, int64_t end, int64_t step) { + return at::_ops::slice_backward::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, start, end, step); +} +namespace symint { + template >> + at::Tensor slice_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t start, int64_t end, int64_t step) { + return at::_ops::slice_backward::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, start, end, step); + } +} + +// aten::slice_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step) -> Tensor +inline at::Tensor slice_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step) { + return at::_ops::slice_backward::call(grad_output, input_sizes, dim, start, end, step); +} +namespace symint { + template >> + at::Tensor slice_backward(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step) { + return at::_ops::slice_backward::call(grad_output, input_sizes, dim, start, end, step); + } +} + +// aten::slice_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t start, int64_t end, int64_t step) { + return at::_ops::slice_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, start, end, step, out); +} +namespace symint { + template >> + at::Tensor & slice_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t start, int64_t end, int64_t step) { + return at::_ops::slice_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, start, end, step, out); + } +} + +// aten::slice_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t start, int64_t end, int64_t step, at::Tensor & out) { + return at::_ops::slice_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, start, end, step, out); +} +namespace symint { + template >> + at::Tensor & slice_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t start, int64_t end, int64_t step, at::Tensor & out) { + return at::_ops::slice_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, start, end, step, out); + } +} + +// aten::slice_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_backward_symint_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step) { + return at::_ops::slice_backward_out::call(grad_output, input_sizes, dim, start, end, step, out); +} +namespace symint { + template >> + at::Tensor & slice_backward_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step) { + return at::_ops::slice_backward_out::call(grad_output, input_sizes, dim, start, end, step, out); + } +} + +// aten::slice_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slice_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step, at::Tensor & out) { + return at::_ops::slice_backward_out::call(grad_output, input_sizes, dim, start, end, step, out); +} +namespace symint { + template >> + at::Tensor & slice_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step, at::Tensor & out) { + return at::_ops::slice_backward_out::call(grad_output, input_sizes, 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_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1543c877854515005bf78e082d86a483debb5fd1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_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(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1); +TORCH_API 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); + +} // 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_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ffadb5d5a15c03783705e97f2edb4d4573b302d4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_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 & slice_copy_Tensor_out_symint(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out); +TORCH_API at::Tensor slice_copy_Tensor_symint(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=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/slice_copy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a002b127d1db604e6f78abbf3f89a763cdf1b8f3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_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 slice_copy_Tensor { + using schema = 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_copy"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step); +}; + +struct TORCH_API slice_copy_Tensor_out { + using schema = 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_copy"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "slice_copy.Tensor_out(Tensor self, 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, 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, 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/slice_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cfc94157d6a08eabc99d7a498b422bfda11a57f3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_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 slice(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=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/slice_scatter_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_scatter_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b2a0adfb9781d12c71882f759dcc35195ca2672b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slice_scatter_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 slice_scatter(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_scatter_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 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/slogdet.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet.h new file mode 100644 index 0000000000000000000000000000000000000000..4a1e8ded928a6bb66a93e99868794ab4c18600ca --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet.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::slogdet(Tensor self) -> (Tensor sign, Tensor logabsdet) +inline ::std::tuple slogdet(const at::Tensor & self) { + return at::_ops::slogdet::call(self); +} + +// aten::slogdet.out(Tensor self, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) +inline ::std::tuple slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, const at::Tensor & self) { + return at::_ops::slogdet_out::call(self, sign, logabsdet); +} +// aten::slogdet.out(Tensor self, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) +inline ::std::tuple slogdet_outf(const at::Tensor & self, at::Tensor & sign, at::Tensor & logabsdet) { + return at::_ops::slogdet_out::call(self, sign, logabsdet); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e7e2bc00ddcf25e69547b84b632c89fc2026634 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/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 slogdet(const at::Tensor & self); +TORCH_API ::std::tuple slogdet_out(const at::Tensor & self, 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/slow_conv_dilated2d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated2d.h new file mode 100644 index 0000000000000000000000000000000000000000..eb9283bdf174936484d1dce2ff2e5989d5a7743f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated2d.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_dilated2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1) -> Tensor +inline at::Tensor slow_conv_dilated2d(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) { + return at::_ops::slow_conv_dilated2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); +} +namespace symint { + template >> + at::Tensor slow_conv_dilated2d(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) { + return at::_ops::slow_conv_dilated2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); + } +} + +// aten::slow_conv_dilated2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1) -> Tensor +inline at::Tensor slow_conv_dilated2d_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)) { + return at::_ops::slow_conv_dilated2d::call(self, weight, kernel_size, bias, stride, padding, dilation); +} +namespace symint { + template >> + at::Tensor slow_conv_dilated2d(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)) { + return at::_ops::slow_conv_dilated2d::call(self, weight, kernel_size, bias, stride, padding, dilation); + } +} + +// aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_dilated2d_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) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template >> + at::Tensor & slow_conv_dilated2d_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) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_dilated2d_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) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template >> + at::Tensor & slow_conv_dilated2d_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) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_dilated2d_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)) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template >> + at::Tensor & slow_conv_dilated2d_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)) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); + } +} + +// aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & slow_conv_dilated2d_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) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template >> + at::Tensor & slow_conv_dilated2d_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) { + return at::_ops::slow_conv_dilated2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, 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/slow_conv_dilated3d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d.h new file mode 100644 index 0000000000000000000000000000000000000000..86071f1f68944035efbc0158e3e6e8ed9ad6e2c9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d.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_dilated3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1) -> Tensor +inline 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) { + return at::_ops::slow_conv_dilated3d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); +} +namespace symint { + template >> + 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) { + return at::_ops::slow_conv_dilated3d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); + } +} + +// aten::slow_conv_dilated3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1) -> Tensor +inline 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)) { + return at::_ops::slow_conv_dilated3d::call(self, weight, kernel_size, bias, stride, padding, dilation); +} +namespace symint { + template >> + at::Tensor slow_conv_dilated3d(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)) { + return at::_ops::slow_conv_dilated3d::call(self, weight, kernel_size, bias, stride, padding, dilation); + } +} + +// aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template >> + 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) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template >> + 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) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline 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)) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template >> + at::Tensor & slow_conv_dilated3d_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)) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); + } +} + +// aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template >> + at::Tensor & slow_conv_dilated3d_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) { + return at::_ops::slow_conv_dilated3d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, 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/slow_conv_transpose2d_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c9a30f75e32c578eb7309d271f081c6343d812c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_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 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); +TORCH_API 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)); +TORCH_API 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); +TORCH_API 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); +TORCH_API 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)); +TORCH_API 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); + +} // 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_transpose2d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0d8da8f96b66bd5b3ab8b01f477a0545861f90b1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_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_slow_conv_transpose2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Tensor & weight, at::ArrayRef kernel_size, at::OptionalTensorRef bias, at::ArrayRef stride, at::ArrayRef padding, at::ArrayRef output_padding, at::ArrayRef dilation); +}; + +} // 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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d94b24d6bafb66fae711edd4da4bad2acbf9ec8b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_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 smooth_l1_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::smooth_l1_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "smooth_l1_loss.out(Tensor self, Tensor target, int reduction=Mean, float beta=1.0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); +}; + +struct TORCH_API smooth_l1_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::smooth_l1_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "smooth_l1_loss(Tensor self, Tensor target, int reduction=Mean, float beta=1.0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta); +}; + +}} // 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/soft_margin_loss_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/soft_margin_loss_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..54ea0c55d12465b918b338bfde31f792448f0a96 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/soft_margin_loss_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 soft_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API 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); +TORCH_API 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); + +} // 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/softplus_backward_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..152f157be320aa176ded78e75b26151c4e33ecd0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_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 softplus_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold); + +} // 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/softplus_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e9b68ceb0fa693158396bee52e07865728cbf37 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_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 softplus_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold); +TORCH_API 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); +TORCH_API 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); + +} // 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/softplus_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..698ab60556c6662ac8166fb76fb92e958ab09569 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_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 softplus(const at::Tensor & self, const at::Scalar & beta=1, const at::Scalar & threshold=20); +TORCH_API at::Tensor & softplus_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & beta=1, const at::Scalar & threshold=20); +TORCH_API at::Tensor & softplus_outf(const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, 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/softshrink_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..2d72976fbd1e1e553ca48d5675bd0e7ebdb1a022 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_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::softshrink_backward.grad_input(Tensor grad_output, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & softshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd) { + return at::_ops::softshrink_backward_grad_input::call(grad_output, self, lambd, grad_input); +} +// aten::softshrink_backward.grad_input(Tensor grad_output, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & softshrink_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) { + return at::_ops::softshrink_backward_grad_input::call(grad_output, self, lambd, grad_input); +} + +// aten::softshrink_backward(Tensor grad_output, Tensor self, Scalar lambd) -> Tensor +inline at::Tensor softshrink_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd) { + return at::_ops::softshrink_backward::call(grad_output, self, lambd); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f8fba2331db6fd2b3141e31e1567336c9b4161d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_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(const at::Tensor & self, const at::Scalar & lambd=0.5); + +} // 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_compressed_tensor.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_compressed_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..76ab8710e0c25be2496916f3daaaf98ddef82b08 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_compressed_tensor.h @@ -0,0 +1,84 @@ +#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_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_compressed_tensor(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) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor sparse_compressed_tensor(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) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_compressed_tensor_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_compressed_tensor_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) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor sparse_compressed_tensor(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) { + return at::_ops::sparse_compressed_tensor_comp_plain_value_size::call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); + } +} + +// aten::sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::TensorOptions options) { + return at::_ops::sparse_compressed_tensor_comp_plain_value::call(compressed_indices, plain_indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_compressed_tensor_comp_plain_value::call(compressed_indices, plain_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_coo_tensor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_coo_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5786f78369b0c5c21ef7e931bc2739bd8f5f7a40 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_coo_tensor_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 sparse_coo_tensor(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & sparse_coo_tensor_size_out(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor sparse_coo_tensor(const at::Tensor & indices, const at::Tensor & values, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional is_coalesced=::std::nullopt); +TORCH_API at::Tensor sparse_coo_tensor(const at::Tensor & indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional is_coalesced=::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/sparse_csr_tensor_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csr_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9bbe648302399a580e3642a8ae5510dccd6db6cc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csr_tensor_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_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={}); +TORCH_API 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={}); +} // 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_mask_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_mask_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d6c490e38a77b487c6ed1ab833d612bea3b8b59c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_mask_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_mask { + 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::sparse_mask"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sparse_mask(Tensor self, Tensor mask) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mask); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask); +}; + +struct TORCH_API sparse_mask_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::sparse_mask"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sparse_mask.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & 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/sparse_resize_and_clear_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7d1e1c225f72e5cf15669fb11eb87d1dcb287d3c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_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 sparse_resize_and_clear_ { + using schema = const at::Tensor & (const at::Tensor &, at::IntArrayRef, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sparse_resize_and_clear_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sparse_resize_and_clear_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +}; + +struct TORCH_API sparse_resize_and_clear_out { + using schema = const at::Tensor & (const at::Tensor &, at::IntArrayRef, int64_t, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sparse_resize_and_clear"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sparse_resize_and_clear.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!)"; + static const at::Tensor & call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out); +}; + +struct TORCH_API sparse_resize_and_clear { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sparse_resize_and_clear"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "sparse_resize_and_clear(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t 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/sparse_sampled_addmm.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_sampled_addmm.h new file mode 100644 index 0000000000000000000000000000000000000000..5da7dece0abd437f23978965d52078caa909335c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_sampled_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_sampled_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sparse_sampled_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_sampled_addmm_out::call(self, mat1, mat2, beta, alpha, out); +} +// aten::sparse_sampled_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sparse_sampled_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_sampled_addmm_out::call(self, mat1, mat2, beta, alpha, out); +} + +// aten::sparse_sampled_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor sparse_sampled_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_sampled_addmm::call(self, mat1, mat2, beta, alpha); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_sampled_addmm_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_sampled_addmm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..865e1108a0f6e81b887d49a7b5f5d09f8ab4c9ed --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_sampled_addmm_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 sparse_sampled_addmm_sparse_csr_cpu(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_sampled_addmm_out_sparse_csr_cpu(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor sparse_sampled_addmm_sparse_csr_cuda(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_sampled_addmm_out_sparse_csr_cuda(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/special_bessel_j0_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j0_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..b185f5c6ab0b22e6667c0eec009c2562ce53923c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j0_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_bessel_j0 : 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_bessel_y0_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e7e001b9f290292ce2b3945012cd0a3d92d39da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_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_y0(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_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..ad6ab710949f0d6119572bd4345f6d2b58903dc4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y0_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_bessel_y0 : 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_chebyshev_polynomial_t_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..988f0d6adbd87a34d68a45e25e4fde852d10c46b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_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_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_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_chebyshev_polynomial_w_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..422508f18257bb6420c3e4d373e1805c7c85fb95 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_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_chebyshev_polynomial_w(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_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_chebyshev_polynomial_w_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b9bc8012d1a730857a090a86a48e35a26bfaf1e6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w_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_w_out : public at::meta::structured_special_chebyshev_polynomial_w { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_chebyshev_polynomial_w(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_w_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_entr_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_entr_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0b040854890e350ef3c72c74b398c2bca8a0370b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_entr_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_entr : 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_erf_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erf_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e305a3cce5ed12f41fea6a78aa0a94ab536dae7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erf_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_erf(const at::Tensor & self); +TORCH_API at::Tensor & special_erf_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_erf_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_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfcx_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d908ebd508d24003c879324ef90d7ba6940e001e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfcx_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_erfcx { + 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_erfcx"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_erfcx(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_erfcx_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_erfcx"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_erfcx.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_erfinv.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfinv.h new file mode 100644 index 0000000000000000000000000000000000000000..1fb9014cb87e5e1b64a562ae1fb0ea43ef371de7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_erfinv.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_erfinv(Tensor self) -> Tensor +inline at::Tensor special_erfinv(const at::Tensor & self) { + return at::_ops::special_erfinv::call(self); +} + +// aten::special_erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_erfinv_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_erfinv_out::call(self, out); +} +// aten::special_erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_erfinv_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_erfinv_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_exp2_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_exp2_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b37119a0674bdddc81d51645eeb99f57ee4a9779 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_exp2_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_exp2(const at::Tensor & self); +TORCH_API at::Tensor & special_exp2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_exp2_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_gammaincc_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f894cf924d578a4e408aaaacbbbe8b2dbc93c14a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc_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_gammaincc(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_gammaincc_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/special_gammaincc_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..24d3f8730a5cdba47bc1e0bdd73eea86054f6421 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammaincc_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_gammaincc_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_gammaincc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_gammaincc.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 special_gammaincc { + 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_gammaincc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_gammaincc(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/special_hermite_polynomial_h_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..17f30cbc90476aef28f9ad03e9b4f97c9b9b6e8a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_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_hermite_polynomial_h : 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_hermite_polynomial_h_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_native.h new file mode 100644 index 0000000000000000000000000000000000000000..66f948d18fe4e25b36e301d7e7ae32c59c4a7177 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_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_hermite_polynomial_h_out : public at::meta::structured_special_hermite_polynomial_h { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_hermite_polynomial_h(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_h_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_hermite_polynomial_h(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_hermite_polynomial_h_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_hermite_polynomial_he_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ea35bd68a5b4787617be6a1c7aaff6bc5b8f8cae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_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_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 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_i0e_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..271d7113141158cfa9cb578b470445806d3c579c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_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_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 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_i0e_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a4f134874d595c9764272d0cc67a11e36015c998 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i0e_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_i0e { + 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_i0e"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_i0e(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_i0e_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_i0e"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_i0e.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_i1_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..65bcbacf8354e5c0f0259ac5e50220ed8d5a53af --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_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_i1(const at::Tensor & self); +TORCH_API at::Tensor & special_i1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_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_i1_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9a89fefe7934ea65827f8477a505b59edfe1b90e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_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_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_i1"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_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_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_i1"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_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_laguerre_polynomial_l_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..29dc78fc4c1f73d61762a1c77c85d488d79dbdc0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_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_laguerre_polynomial_l(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_laguerre_polynomial_l_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_laguerre_polynomial_l_outf(const at::Tensor & x, const at::Tensor & n, 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_legendre_polynomial_p_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p_native.h new file mode 100644 index 0000000000000000000000000000000000000000..141a01339b577a096d0019f89c705071827e3b00 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p_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_legendre_polynomial_p_out : public at::meta::structured_special_legendre_polynomial_p { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_legendre_polynomial_p(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_legendre_polynomial_p_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_legendre_polynomial_p(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_legendre_polynomial_p_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_log1p_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0f09a3bb4f279c9338728d3b0489019ab707db2a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p_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_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::special_log1p"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_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 special_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::special_log1p"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_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/special_log_ndtr.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr.h new file mode 100644 index 0000000000000000000000000000000000000000..b751a3f063c9340bbec60f295e369c3d774e01ae --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr.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_log_ndtr(Tensor self) -> Tensor +inline at::Tensor special_log_ndtr(const at::Tensor & self) { + return at::_ops::special_log_ndtr::call(self); +} + +// aten::special_log_ndtr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_log_ndtr_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_log_ndtr_out::call(self, out); +} +// aten::special_log_ndtr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_log_ndtr_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_log_ndtr_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_logsumexp_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_logsumexp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..23e68e0a8f1d3a99e36570e5fd7e19d26d3d53da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_logsumexp_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_logsumexp(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & special_logsumexp_out(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, 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_modified_bessel_i1_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..701c6faeb7dd1041e8f4fd0970d06b562b936488 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_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_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 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_modified_bessel_k0_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k0_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d062b5b12b37e32a33d8b405d0864b740e5509fd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k0_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_k0(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_k0_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_k0_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_ndtr_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..53768ac2249a2b193764c4a1ed5bbd1e5f0436b9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_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_ndtr(const at::Tensor & self); +TORCH_API at::Tensor & special_ndtr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_ndtr_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_ndtr_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e46ec674e28b6eff38574a661ddbdfc2f717ca25 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtr_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_ndtr { + 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_ndtr"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_ndtr(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_ndtr_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_ndtr"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_ndtr.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_ndtri_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..893ddf5eab31a48189c4b7c6bdcb7293a945cdaf --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri_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_ndtri(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_polygamma_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_polygamma_native.h new file mode 100644 index 0000000000000000000000000000000000000000..92896c3e88d2b6f77159cae3854a84c0bba6c4f2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_polygamma_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_polygamma(int64_t n, const at::Tensor & self); +TORCH_API at::Tensor & special_polygamma_out(int64_t n, 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_round.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_round.h new file mode 100644 index 0000000000000000000000000000000000000000..a051b45704f6b159a9df14ba2c6720d315fb2ce7 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_round.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_round(Tensor self, *, int decimals=0) -> Tensor +inline at::Tensor special_round(const at::Tensor & self, int64_t decimals=0) { + return at::_ops::special_round::call(self, decimals); +} + +// aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_round_out(at::Tensor & out, const at::Tensor & self, int64_t decimals=0) { + return at::_ops::special_round_out::call(self, decimals, out); +} +// aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_round_outf(const at::Tensor & self, int64_t decimals, at::Tensor & out) { + return at::_ops::special_round_out::call(self, decimals, 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_scaled_modified_bessel_k0_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c49622c30a2866ce3e864881909388a44c3a974 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_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_scaled_modified_bessel_k0(const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k0_out(at::Tensor & out, const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k0_outf(const at::Tensor & x, 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_scaled_modified_bessel_k0_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..654795a177530bbdae59130ea0c37570b7c14632 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_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_scaled_modified_bessel_k0 : public TensorIteratorBase { + + + void meta(const at::Tensor & x); +}; + +} // 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_scaled_modified_bessel_k0_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1346b04dee9ef5d1c70d7ed9c990980eb5ec0a36 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_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_scaled_modified_bessel_k0_out : public at::meta::structured_special_scaled_modified_bessel_k0 { +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_scaled_modified_bessel_k0_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..77eca21e68d777e70f5e825349743045035469ba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_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_scaled_modified_bessel_k0 { + 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_scaled_modified_bessel_k0"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_scaled_modified_bessel_k0(Tensor x) -> Tensor"; + static at::Tensor call(const at::Tensor & x); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x); +}; + +struct TORCH_API special_scaled_modified_bessel_k0_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_scaled_modified_bessel_k0"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, 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_k1_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8a95b70f29eabaf473cf8e55abaf10f7fc14193b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_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_scaled_modified_bessel_k1(const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k1_out(at::Tensor & out, const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k1_outf(const at::Tensor & x, 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_scaled_modified_bessel_k1_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..20a3761f49ecbe26446c72352a3fc5fb136c19b8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_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_scaled_modified_bessel_k1 : public TensorIteratorBase { + + + void meta(const at::Tensor & x); +}; + +} // 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_shifted_chebyshev_polynomial_u.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u.h new file mode 100644 index 0000000000000000000000000000000000000000..44055a5c1b07ae914e151448a3afbb0640dcf64a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u.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_u(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_u(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_u::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_u(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_u_x_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_u(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_u_n_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_u_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_u_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_u_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_u_x_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_u_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_u_x_scalar_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_u_n_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_u_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_u_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_u_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f53a7b2ba7d9b38a06ecd3f1cd02ecef69bd3f32 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_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_u(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_u(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_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_u_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0bf524340368173cefa219ab9263f15046d278a2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_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_u(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_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_v_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1dd1e1b5882c58e1f33e7f9e7000f11fb1e4663c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_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_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 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_shifted_chebyshev_polynomial_w.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_w.h new file mode 100644 index 0000000000000000000000000000000000000000..e922c48d920afac9a63b97b35a8b16930b314167 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_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_shifted_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_w(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_w::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_w(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_w_x_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_shifted_chebyshev_polynomial_w(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_w_n_scalar::call(x, n); +} + +// aten::special_shifted_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_w_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_w_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_w_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_shifted_chebyshev_polynomial_w_x_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_w_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_shifted_chebyshev_polynomial_w_x_scalar_out::call(x, n, out); +} + +// aten::special_shifted_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_shifted_chebyshev_polynomial_w_n_scalar_out::call(x, n, out); +} +// aten::special_shifted_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_shifted_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_shifted_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_sinc_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_sinc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a4ee17ebdab558fe50b32c510c487e200fb4a8fc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_sinc_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_sinc(const at::Tensor & self); +TORCH_API at::Tensor & special_sinc_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_softmax_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e618b411e8e205d4d46a665cfeb80c46b2ebd5b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax_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 special_softmax { + 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::special_softmax"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_softmax(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); +}; + +}} // 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_spherical_bessel_j0_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..276517645e8cef310e04daf020ae6d72218c2ba3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_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_spherical_bessel_j0(const at::Tensor & x); +TORCH_API at::Tensor & special_spherical_bessel_j0_out(at::Tensor & out, const at::Tensor & x); +TORCH_API at::Tensor & special_spherical_bessel_j0_outf(const at::Tensor & x, 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_spherical_bessel_j0_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..3e8631eb4f2ce2e67cba4f12f83fb26796dff14d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_spherical_bessel_j0_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_spherical_bessel_j0 : public TensorIteratorBase { + + + void meta(const at::Tensor & x); +}; + +} // 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_xlogy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlogy.h new file mode 100644 index 0000000000000000000000000000000000000000..02969cfdad7afa1b94532e14fe5437d17eea72f8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlogy.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_xlogy(Tensor self, Tensor other) -> Tensor +inline at::Tensor special_xlogy(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_xlogy::call(self, other); +} + +// aten::special_xlogy.self_scalar(Scalar self, Tensor other) -> Tensor +inline at::Tensor special_xlogy(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_xlogy_self_scalar::call(self, other); +} + +// aten::special_xlogy.other_scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor special_xlogy(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_xlogy_other_scalar::call(self, other); +} + +// aten::special_xlogy.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlogy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_xlogy_out::call(self, other, out); +} +// aten::special_xlogy.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlogy_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_xlogy_out::call(self, other, out); +} + +// aten::special_xlogy.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlogy_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_xlogy_self_scalar_out::call(self, other, out); +} +// aten::special_xlogy.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlogy_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_xlogy_self_scalar_out::call(self, other, out); +} + +// aten::special_xlogy.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlogy_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_xlogy_other_scalar_out::call(self, other, out); +} +// aten::special_xlogy.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlogy_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::special_xlogy_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_xlogy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlogy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dce11d82c956882ee5e19c9402a5c49a83790f26 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_xlogy_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_xlogy { + 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_xlogy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_xlogy(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 special_xlogy_self_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_xlogy"; + static constexpr const char* overload_name = "self_scalar"; + static constexpr const char* schema_str = "special_xlogy.self_scalar(Scalar self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API special_xlogy_other_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_xlogy"; + static constexpr const char* overload_name = "other_scalar"; + static constexpr const char* schema_str = "special_xlogy.other_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 special_xlogy_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_xlogy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_xlogy.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 special_xlogy_self_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_xlogy"; + static constexpr const char* overload_name = "self_scalar_out"; + static constexpr const char* schema_str = "special_xlogy.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API special_xlogy_other_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_xlogy"; + static constexpr const char* overload_name = "other_scalar_out"; + static constexpr const char* schema_str = "special_xlogy.other_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/special_zeta_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3c1883ce5cd5af9af51a7b3ff888a0876d53a3f9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/special_zeta_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_zeta { + 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_zeta"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_zeta(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 special_zeta_self_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_zeta"; + static constexpr const char* overload_name = "self_scalar"; + static constexpr const char* schema_str = "special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API special_zeta_other_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_zeta"; + static constexpr const char* overload_name = "other_scalar"; + static constexpr const char* schema_str = "special_zeta.other_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 special_zeta_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_zeta"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_zeta.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 special_zeta_self_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_zeta"; + static constexpr const char* overload_name = "self_scalar_out"; + static constexpr const char* schema_str = "special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API special_zeta_other_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_zeta"; + static constexpr const char* overload_name = "other_scalar_out"; + static constexpr const char* schema_str = "special_zeta.other_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/split_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b7d35a8dcf44c108ff71282b968eb992fd02e820 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_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 split(const at::Tensor & self, int64_t split_size, int64_t dim=0); +TORCH_API ::std::vector split_symint(const at::Tensor & self, c10::SymIntArrayRef split_size, 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/split_with_sizes_copy_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..956c84486679318734926641bff3de0101b2f09d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_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 ::std::vector split_with_sizes_copy(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +TORCH_API ::std::vector split_with_sizes_copy_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=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/split_with_sizes_copy_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6c401501470458a7a94832fdc8a38d9b8729c9c2 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_copy_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 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 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/sqrt_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..47f720bd4ba2dc0a15f3d0e761a72cc2f974e520 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_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 sqrt(const at::Tensor & self); +TORCH_API at::Tensor & sqrt_(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/square_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/square_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c68ffc9f32035a442900f68e03f779d1ba1de3c1 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/square_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 square(const at::Tensor & self); +TORCH_API at::Tensor & square_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & square_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & square_(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/squeeze_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..549c282cf814994c9e8527cf7725b7a418fd0d00 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_copy_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 & squeeze_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor squeeze_copy(const at::Tensor & self); +TORCH_API at::Tensor & squeeze_copy_dim_out(const at::Tensor & self, int64_t dim, at::Tensor & out); +TORCH_API at::Tensor squeeze_copy_dim(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & squeeze_copy_dims_out(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +TORCH_API at::Tensor squeeze_copy_dims(const 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/std.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std.h new file mode 100644 index 0000000000000000000000000000000000000000..e8398f0ed674d5f70365737db4bf48b101afc708 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/std.h @@ -0,0 +1,92 @@ +#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::std(Tensor self, bool unbiased=True) -> Tensor +inline at::Tensor std(const at::Tensor & self, bool unbiased) { + return at::_ops::std::call(self, unbiased); +} + +// aten::std.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> Tensor +inline at::Tensor std(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false) { + return at::_ops::std_dim::call(self, dim, unbiased, keepdim); +} + +// aten::std.correction(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False) -> Tensor +inline at::Tensor std(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false) { + return at::_ops::std_correction::call(self, dim, correction, keepdim); +} + +// aten::std.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false) { + return at::_ops::std_out::call(self, dim, unbiased, keepdim, out); +} +// aten::std.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out) { + return at::_ops::std_out::call(self, dim, unbiased, keepdim, out); +} + +// aten::std.correction_out(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false) { + return at::_ops::std_correction_out::call(self, dim, correction, keepdim, out); +} +// aten::std.correction_out(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out) { + return at::_ops::std_correction_out::call(self, dim, correction, keepdim, out); +} + +// aten::std.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> Tensor +inline at::Tensor std(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false) { + return at::_ops::std_names_dim::call(self, dim, unbiased, keepdim); +} + +// aten::std.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false) { + return at::_ops::std_names_out::call(self, dim, unbiased, keepdim, out); +} +// aten::std.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_outf(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out) { + return at::_ops::std_names_out::call(self, dim, unbiased, keepdim, out); +} + +// aten::std.correction_names(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False) -> Tensor +inline at::Tensor std(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false) { + return at::_ops::std_correction_names::call(self, dim, correction, keepdim); +} + +// aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false) { + return at::_ops::std_correction_names_out::call(self, dim, correction, keepdim, out); +} +// aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & std_outf(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim, at::Tensor & out) { + return at::_ops::std_correction_names_out::call(self, dim, correction, keepdim, 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/stride.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stride.h new file mode 100644 index 0000000000000000000000000000000000000000..fd7a212106e49b2e5efbd8b220b4248c058f5f65 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stride.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::stride.int(Tensor self, int dim) -> int +inline int64_t __dispatch_stride(const at::Tensor & self, int64_t dim) { + return at::_ops::stride_int::call(self, dim); +} + +// aten::stride.Dimname(Tensor self, Dimname dim) -> int +inline int64_t stride(const at::Tensor & self, at::Dimname dim) { + return at::_ops::stride_Dimname::call(self, 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/stride_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stride_native.h new file mode 100644 index 0000000000000000000000000000000000000000..47e526b0c0d43f3932df178b403cbb5af836d198 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/stride_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 int64_t stride(const at::Tensor & self, int64_t dim); +TORCH_API int64_t stride(const at::Tensor & self, at::Dimname 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/sum_to_size_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sum_to_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4a6e20a1246c22fdfca56515c0063caf8ff86e19 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sum_to_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 at::Tensor sum_to_size_symint(const at::Tensor & self, c10::SymIntArrayRef 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/sym_numel.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_numel.h new file mode 100644 index 0000000000000000000000000000000000000000..25adac1f4756f60db7bce474bd37b38f804e9549 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_numel.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_numel(Tensor self) -> SymInt +inline c10::SymInt __dispatch_sym_numel(const at::Tensor & self) { + return at::_ops::sym_numel::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/sym_size_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..20153ed6c0d90bc8c5efe0a43623997c5e6444b6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_size_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::SymInt sym_size(const at::Tensor & self, int64_t 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/sym_stride.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_stride.h new file mode 100644 index 0000000000000000000000000000000000000000..325fd0ebfb1ac475a49630588921ab9936aeecb6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/sym_stride.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_stride.int(Tensor self, int dim) -> SymInt +inline c10::SymInt __dispatch_sym_stride(const at::Tensor & self, int64_t dim) { + return at::_ops::sym_stride_int::call(self, 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/t_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c41cd69b5c83bba60c2a4ff69e9d06013be36dce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/t_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 & t_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & t_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/take_along_dim.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/take_along_dim.h new file mode 100644 index 0000000000000000000000000000000000000000..ac148fcd16dfad3c54008385efe7dc4c3f3c97ac --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/take_along_dim.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::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_along_dim_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim=::std::nullopt) { + return at::_ops::take_along_dim_out::call(self, indices, dim, out); +} +// aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_along_dim_outf(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out) { + return at::_ops::take_along_dim_out::call(self, indices, dim, out); +} + +// aten::take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor +inline at::Tensor take_along_dim(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim=::std::nullopt) { + return at::_ops::take_along_dim::call(self, indices, 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/take_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/take_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3f90b69c17e9b63b0e1da8a099bef5ef2e07269e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/take_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 take(const at::Tensor & self, const at::Tensor & index); +TORCH_API at::Tensor & take_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index); +TORCH_API at::Tensor & take_outf(const at::Tensor & self, 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/tanh_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..efea6f55539dbc421283d65fd240ced738bae1a3 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_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_tanh_backward_out : public at::meta::structured_tanh_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & output, 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/tanh_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..51088afdcdc854caaa31cf6ebf9fb2a71f7ff6ea --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tanh_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 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 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/threshold_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8fb6ee8e4997fcb4d01b39a8641f8baae361e8fe --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_backward_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_threshold_backward_out : public at::meta::structured_threshold_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, const at::Tensor & grad_input); +}; +TORCH_API at::Tensor threshold_backwards_nested(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +TORCH_API at::Tensor threshold_backward_sparse(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +TORCH_API at::Tensor & threshold_backward_sparse_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, at::Tensor & grad_input); +TORCH_API at::Tensor threshold_backward_sparse_compressed(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +TORCH_API at::Tensor & threshold_backward_sparse_compressed_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, at::Tensor & grad_input); +TORCH_API at::Tensor mkldnn_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +} // 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_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..bab5a486fc7fb411cf7fb99c446dcb51218ef1da --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_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_threshold : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & 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/to_dense_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2a2f9dc9f43ec442fec6aebe50232958fda78edc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_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 to_dense_backward { + 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::to_dense_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "to_dense_backward(Tensor grad, Tensor input, bool? masked_grad=None) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & input, ::std::optional masked_grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input, ::std::optional masked_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/to_mkldnn_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63e187e2de81e46852f31e16aed342475cd29f3b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_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 to_mkldnn_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::to_mkldnn_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "to_mkldnn_backward(Tensor grad, Tensor input) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & input); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input); +}; + +}} // 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_csc_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a211c797eb1053b286057512918daebdb7075a2f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc_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 to_sparse_csc { + 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_sparse_csc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dense_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::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/to_sparse_csr_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6b8e68feeaab993b482ef46f2a3bb95fab9200b4 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csr_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 to_sparse_csr(const at::Tensor & self, ::std::optional dense_dim=::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/trace_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..36ec0c75c905bda659c48a8983c08776419d4997 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward.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::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor +inline at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, c10::fromIntArrayRefSlow(sizes)); +} +namespace symint { + template >> + at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, c10::fromIntArrayRefSlow(sizes)); + } +} + +// aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor +inline at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, sizes); +} +namespace symint { + template >> + at::Tensor trace_backward(const at::Tensor & grad, c10::SymIntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, sizes); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b840392e5769f0d947969b2e45278309a9a10877 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_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 transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1); + +} // 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/transpose_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_native.h new file mode 100644 index 0000000000000000000000000000000000000000..021d6a19207b94669f5896c6ef4690bc798db86e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/transpose_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 transpose(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor transpose_nested(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor & transpose_(at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname 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/trapezoid_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trapezoid_native.h new file mode 100644 index 0000000000000000000000000000000000000000..352e927866f9450609468204278683611fb8519f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trapezoid_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 trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1); +TORCH_API at::Tensor trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-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/triangular_solve.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve.h new file mode 100644 index 0000000000000000000000000000000000000000..8397b8da0ae9fdcb85455181bac16133b3c3ee4c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_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::triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient) +inline ::std::tuple triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false) { + return at::_ops::triangular_solve_X::call(self, A, upper, transpose, unitriangular, X, M); +} +// aten::triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient) +inline ::std::tuple triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M) { + return at::_ops::triangular_solve_X::call(self, A, upper, transpose, unitriangular, X, M); +} + +// aten::triangular_solve(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False) -> (Tensor solution, Tensor cloned_coefficient) +inline ::std::tuple triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false) { + return at::_ops::triangular_solve::call(self, A, upper, transpose, unitriangular); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2de11a09ba7413821ed185217e8d141808f715ce --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_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 ::std::tuple triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false); +TORCH_API ::std::tuple triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false); +TORCH_API ::std::tuple triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); + +} // 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_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad57759933764d4bd8e77aeab74e27c7a57833dc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_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 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_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); +TORCH_API at::Tensor & tril_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt diagonal=0); +TORCH_API at::Tensor & tril_symint_outf(const at::Tensor & self, c10::SymInt diagonal, at::Tensor & out); +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 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_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..409519cacde73e61838b71c389ae45b116a1d4a0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/tril_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_tril : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, int64_t diagonal); +}; + +} // 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/triu_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c166462e634cc03da8864cb52ecee12bafae5e5b --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/triu_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 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_(at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & triu__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/trunc_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..925490a3956663ac004060ab29ce80f7eddb3fe8 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_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 trunc(const at::Tensor & self); +TORCH_API at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & trunc_(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/trunc_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..743d8b6d766b5c72f97ae071b5ad79e77ba67562 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_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_trunc : 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/trunc_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2adff4d447bc4893160537250347d57718374ece --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_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_trunc_out : public at::meta::structured_trunc { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor trunc_sparse(const at::Tensor & self); +TORCH_API at::Tensor & trunc_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & trunc_sparse_(at::Tensor & self); +TORCH_API at::Tensor trunc_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & trunc_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & trunc_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/trunc_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0794d44241b1529c5f38b8f0337d2b8901a7ae95 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/trunc_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 trunc { + 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::trunc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "trunc(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 trunc_ { + 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::trunc_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "trunc_(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 trunc_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::trunc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "trunc.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/type_as.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as.h new file mode 100644 index 0000000000000000000000000000000000000000..c8e0c64940d461b0622eb1dfca5209590d0380e9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as.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/type_as_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as_native.h new file mode 100644 index 0000000000000000000000000000000000000000..84634023dbe4f6d18353093801f4aab41515def9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/type_as_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 type_as(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/unfold_backward_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5b3f492ea23c4a96edb3f08cf7cb32c0ab0c975a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_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 & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step); +TORCH_API at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out); +TORCH_API at::Tensor & unfold_backward_symint_out(at::Tensor & out, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step); +TORCH_API at::Tensor & unfold_backward_symint_outf(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, 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_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3286b25b1a3b9b6f4407c9cda364f6fc188ca365 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_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 unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step); +TORCH_API at::Tensor unfold_backward_symint(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, 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/unfold_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6ba9d44963291b529b2fc305770bd007cb1b5bba --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_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 & unfold_copy_out(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out); +TORCH_API at::Tensor unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); +} // 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/unique_consecutive_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b33d6dcc1c344c9eaabda03de95ad7649bf7f41e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unique_consecutive_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 unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional 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/unique_consecutive_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unique_consecutive_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e321f6b987bce68c720c0ffab468963b52b24914 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unique_consecutive_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 unique_consecutive { + 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::unique_consecutive"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "unique_consecutive(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional dim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional dim); +}; + +struct TORCH_API unique_consecutive_out { + 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::unique_consecutive"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "unique_consecutive.out(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional dim, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional dim, 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/unique_dim_consecutive_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unique_dim_consecutive_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aabb17a39c54eceeb84a7c9f388803acaa26f12c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unique_dim_consecutive_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 unique_dim_consecutive(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=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/unsafe_chunk_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_chunk_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7834b9fdafa5089109c5e2d0bfde9f562d7e65b0 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_chunk_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 unsafe_chunk(const at::Tensor & self, int64_t chunks, 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/unsafe_split_with_sizes_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..31b1ef26cf6ef66bb4b1154615aaffa42c9c8cbd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_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_with_sizes { + using schema = ::std::vector (const at::Tensor &, c10::SymIntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::unsafe_split_with_sizes"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]"; + static ::std::vector call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim); +}; + +struct TORCH_API unsafe_split_with_sizes_out { + using schema = void (const at::Tensor &, c10::SymIntArrayRef, 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_with_sizes"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()"; + static void call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, 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/unsqueeze.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze.h new file mode 100644 index 0000000000000000000000000000000000000000..df0f0d4d11613485c2624c7ee7b485cabc298208 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze.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::unsqueeze(Tensor(a) self, int dim) -> Tensor(a) +inline at::Tensor unsqueeze(const at::Tensor & self, int64_t dim) { + return at::_ops::unsqueeze::call(self, 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/unsqueeze_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00851cbcdbb8d0332e35ce9d923c78425cc47a0f --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_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 unsqueeze(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & unsqueeze_(at::Tensor & self, int64_t 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/unsqueeze_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fcfd8458b0ea2f9f5350058df81036817f242295 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/unsqueeze_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 & unsqueeze_copy_out(const at::Tensor & self, int64_t dim, at::Tensor & out); +TORCH_API at::Tensor unsqueeze_copy(const at::Tensor & self, 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/upsample_bicubic2d_backward_cuda_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..173fc82eebb383b7fbc07bd2f1ca11cb4b1eee44 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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_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 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_backward_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..aefc2b33321600afc15565f6f4016088716cae40 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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 upsample_bicubic2d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, 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_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "upsample_bicubic2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(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); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API upsample_bicubic2d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, 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_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_bicubic2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_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_bicubic2d_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c1a3374e93b41491d0cb65acb35406f31c0c878 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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_bicubic2d(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_symint(const at::Tensor & self, c10::SymIntArrayRef output_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_bicubic2d_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8cdc9d3ac5b3d2dbdfe80644e1bdd0685c3a8822 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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(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_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_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_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_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_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_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8df5f990b4b9ac40643e7ab350de394bce7c6688 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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 { +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_vec_out_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors, at::Tensor & out); +struct TORCH_API structured_upsample_bilinear2d_out_cpu : public at::meta::structured_upsample_bilinear2d { +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_out_cuda : public at::meta::structured_upsample_bilinear2d { +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); +}; +TORCH_API at::Tensor upsample_bilinear2d_quantized_cpu(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::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/upsample_linear1d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..6bf17a9c4a00c5ec0bb071d41229ec6183d0f539 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_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_linear1d_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); +}; + +} // 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_linear1d_backward_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..37114ae8ff7f7612168de7a7c529cec27e490e1d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_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_upsample_linear1d_backward_out_cpu : public at::meta::structured_upsample_linear1d_backward { +void impl(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, ::std::optional scales, const at::Tensor & grad_input); +}; +struct TORCH_API structured_upsample_linear1d_backward_out_cuda : public at::meta::structured_upsample_linear1d_backward { +void impl(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, ::std::optional scales, 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/upsample_nearest1d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d.h new file mode 100644 index 0000000000000000000000000000000000000000..389a9f180043415daa024a6a9a835f93372b267c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d.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_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); + } +} + +// aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_nearest1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest1d_vec::call(input, output_size, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest1d_vec::call(input, output_size, scale_factors); + } +} + +// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); + } +} + +// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); + } +} + +// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out); + } +} + +// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out); + } +} + +// aten::upsample_nearest1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor +inline at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d::call(self, c10::fromIntArrayRefSlow(output_size), scales); +} +namespace symint { + template >> + at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d::call(self, c10::fromIntArrayRefSlow(output_size), scales); + } +} + +// aten::upsample_nearest1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor +inline at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d::call(self, output_size, scales); +} +namespace symint { + template >> + at::Tensor upsample_nearest1d(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_nearest1d::call(self, output_size, scales); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#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_backward_cpu_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..437dff895a4b8da0667d42f818c749f222729f0e --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_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_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales, 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/upsample_nearest1d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..12686ac2022b78af3dfa150e2695bb1384035cbd --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_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_nearest1d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, ::std::optional scales); +}; + +} // 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_nearest1d_backward_meta_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4f8eef1267d118d2e81f7bd2e8959843e9673d4c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_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_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales, 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_nearest1d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..a1ca55c19d7e0f84b8b2987e5f8ada665647d2f5 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_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_nearest1d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales); +}; + +} // 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_nearest1d_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..302b5b60a61f5edf5fb5aa89d2813f903378dbe6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest1d_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_nearest1d_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_nearest1d"; + static constexpr const char* overload_name = "vec"; + static constexpr const char* schema_str = "upsample_nearest1d.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_nearest1d_out { + using schema = at::Tensor & (const 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::upsample_nearest1d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out); +}; + +struct TORCH_API upsample_nearest1d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_nearest1d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_nearest1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales); +}; + +}} // 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_nearest2d.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d.h new file mode 100644 index 0000000000000000000000000000000000000000..bbaf23048ae7105b230a8a06ad2be99a6af1992c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d.h @@ -0,0 +1,163 @@ +#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_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_nearest2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_nearest2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); + } +} + +// aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_nearest2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec::call(input, output_size, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_nearest2d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec::call(input, output_size, scale_factors); + } +} + +// aten::upsample_nearest2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_nearest2d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales_h, scales_w, out); +} +namespace symint { + template >> + 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) { + return at::_ops::upsample_nearest2d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales_h, scales_w, out); + } +} + +// aten::upsample_nearest2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_nearest2d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_nearest2d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales_h, scales_w, out); + } +} + +// aten::upsample_nearest2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_nearest2d_out::call(self, output_size, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest2d_out::call(self, output_size, scales_h, scales_w, out); + } +} + +// aten::upsample_nearest2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_nearest2d_out::call(self, output_size, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::upsample_nearest2d_out::call(self, output_size, scales_h, scales_w, out); + } +} + +// aten::upsample_nearest2d(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest2d::call(self, c10::fromIntArrayRefSlow(output_size), scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest2d::call(self, c10::fromIntArrayRefSlow(output_size), scales_h, scales_w); + } +} + +// aten::upsample_nearest2d(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::upsample_nearest2d::call(self, output_size, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_nearest2d(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest2d::call(self, output_size, scales_h, scales_w); + } +} + +// aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors, out); + } +} + +// aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_outf(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors, at::Tensor & out) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_outf(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors, at::Tensor & out) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors, out); + } +} + +// aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size, scale_factors, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size, scale_factors, out); + } +} + +// aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors, at::Tensor & out) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size, scale_factors, out); +} +namespace symint { + template >> + at::Tensor & upsample_nearest2d_outf(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors, at::Tensor & out) { + return at::_ops::upsample_nearest2d_vec_out::call(input, output_size, scale_factors, 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/upsample_nearest2d_backward_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..74e473789eee2e45465cb0b88b3627005d9a860a --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_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_nearest2d_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_trilinear3d_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..ba1e1d2d9f660adabc90ad7fbcac651e9a970ea6 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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_trilinear3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + 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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_trilinear3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + 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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_trilinear3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & upsample_trilinear3d_backward_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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_trilinear3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template >> + at::Tensor & upsample_trilinear3d_backward_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) { + return at::_ops::upsample_trilinear3d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_trilinear3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::upsample_trilinear3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_d, scales_h, scales_w); +} +namespace symint { + template >> + 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) { + return at::_ops::upsample_trilinear3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_d, scales_h, scales_w); + } +} + +// aten::upsample_trilinear3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::upsample_trilinear3d_backward::call(grad_output, output_size, input_size, align_corners, scales_d, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_trilinear3d_backward(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) { + return at::_ops::upsample_trilinear3d_backward::call(grad_output, output_size, input_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_compositeexplicitautogradnonfunctional_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4317ed8cb66c432c22c87b40591e147e3d8c0621 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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_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); + +} // 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_trilinear3d_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..36b1f6b33beac561a2d3475590888e25bde7a9fc --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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_trilinear3d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::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/value_selecting_reduction_backward.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/value_selecting_reduction_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..31c4167ef52d72a3ed566528fd80cf3214d642a9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/value_selecting_reduction_backward.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::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, SymInt[] sizes, bool keepdim) -> Tensor +inline at::Tensor value_selecting_reduction_backward(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, at::IntArrayRef sizes, bool keepdim) { + return at::_ops::value_selecting_reduction_backward::call(grad, dim, indices, c10::fromIntArrayRefSlow(sizes), keepdim); +} +namespace symint { + template >> + at::Tensor value_selecting_reduction_backward(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, at::IntArrayRef sizes, bool keepdim) { + return at::_ops::value_selecting_reduction_backward::call(grad, dim, indices, c10::fromIntArrayRefSlow(sizes), keepdim); + } +} + +// aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, SymInt[] sizes, bool keepdim) -> Tensor +inline at::Tensor value_selecting_reduction_backward_symint(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, c10::SymIntArrayRef sizes, bool keepdim) { + return at::_ops::value_selecting_reduction_backward::call(grad, dim, indices, sizes, keepdim); +} +namespace symint { + template >> + at::Tensor value_selecting_reduction_backward(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, c10::SymIntArrayRef sizes, bool keepdim) { + return at::_ops::value_selecting_reduction_backward::call(grad, dim, indices, sizes, 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/value_selecting_reduction_backward_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/value_selecting_reduction_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d36bf74f1321f1af544716ff916eca3f79902a9c --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/value_selecting_reduction_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 value_selecting_reduction_backward(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, at::IntArrayRef sizes, bool keepdim); +TORCH_API at::Tensor value_selecting_reduction_backward_symint(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, c10::SymIntArrayRef sizes, bool keepdim); + +} // 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/var_mean_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_native.h new file mode 100644 index 0000000000000000000000000000000000000000..816bf84c37b09666c29ea4a686f8da500c54a784 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_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 var_mean(const at::Tensor & self, bool unbiased=true); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased=true, bool keepdim=false); +TORCH_API ::std::tuple var_mean_correction_out(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::DimnameList dim, bool unbiased=true, bool keepdim=false); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, 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/view_as_complex_copy_compositeexplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6ef9119defc4bc816254885cda7ffb786474720d --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_complex_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 & view_as_complex_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & view_as_complex_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/view_as_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b087a8e9dfc29c955f7151ef6f2251c32b4341f9 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_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 view_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::view_as"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "view_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/view_as_real_copy_native.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..37c82a432d26fe6ecd85d97484205f8294ba2f81 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_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 & view_as_real_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor view_as_real_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/view_copy.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..6c5bae444bc61bc7d9f2ff505feede9256d76d88 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy.h @@ -0,0 +1,111 @@ +#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_copy(Tensor self, SymInt[] size) -> Tensor +inline at::Tensor view_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy::call(self, c10::fromIntArrayRefSlow(size)); +} +namespace symint { + template >> + at::Tensor view_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy::call(self, c10::fromIntArrayRefSlow(size)); + } +} + +// aten::view_copy(Tensor self, SymInt[] size) -> Tensor +inline at::Tensor view_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy::call(self, size); +} +namespace symint { + template >> + at::Tensor view_copy(const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy::call(self, size); + } +} + +// aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor +inline at::Tensor view_copy(const at::Tensor & self, at::ScalarType dtype) { + return at::_ops::view_copy_dtype::call(self, dtype); +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & view_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy_out::call(self, size, out); +} +namespace symint { + template >> + at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy_out::call(self, size, out); + } +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, size, out); +} +namespace symint { + template >> + at::Tensor & view_copy_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, size, out); + } +} + +// aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::ScalarType dtype) { + return at::_ops::view_copy_dtype_out::call(self, dtype, out); +} +// aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_outf(const at::Tensor & self, at::ScalarType dtype, at::Tensor & out) { + return at::_ops::view_copy_dtype_out::call(self, 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/xlogy_meta.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/xlogy_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..2e2626e28358e9c8d842bd76f83ba1ba9cbe0503 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/xlogy_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_xlogy_Tensor : 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/xlogy_ops.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/xlogy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..de881978ddf8b9898e0ce21650cc77459c7b1601 --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/xlogy_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 xlogy_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::xlogy"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "xlogy.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 xlogy_Scalar_Self { + 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::xlogy"; + static constexpr const char* overload_name = "Scalar_Self"; + static constexpr const char* schema_str = "xlogy.Scalar_Self(Scalar self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API xlogy_Scalar_Other { + 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::xlogy"; + static constexpr const char* overload_name = "Scalar_Other"; + static constexpr const char* schema_str = "xlogy.Scalar_Other(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 xlogy__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::xlogy_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "xlogy_.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 xlogy__Scalar_Other { + 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::xlogy_"; + static constexpr const char* overload_name = "Scalar_Other"; + static constexpr const char* schema_str = "xlogy_.Scalar_Other(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 xlogy_OutTensor { + 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::xlogy"; + static constexpr const char* overload_name = "OutTensor"; + static constexpr const char* schema_str = "xlogy.OutTensor(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 xlogy_OutScalar_Self { + 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::xlogy"; + static constexpr const char* overload_name = "OutScalar_Self"; + static constexpr const char* schema_str = "xlogy.OutScalar_Self(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API xlogy_OutScalar_Other { + 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::xlogy"; + static constexpr const char* overload_name = "OutScalar_Other"; + static constexpr const char* schema_str = "xlogy.OutScalar_Other(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/xor_compositeimplicitautograd_dispatch.h b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/xor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9a70f0c795309fe590f14d6e2ebd5faf47adc1ab --- /dev/null +++ b/URSA/.venv_ursa/lib/python3.12/site-packages/torch/include/ATen/ops/xor_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 __xor__(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & __ixor__(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor __xor__(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & __ixor__(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)