diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h new file mode 100644 index 0000000000000000000000000000000000000000..848ddc0ba5978505aad7577a45d2bc1c5e618efb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.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::_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int +inline 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) { + return at::_ops::_cslt_sparse_mm_search::call(compressed_A, dense_B, bias, alpha, out_dtype, transpose_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..410d06989f7c48bb8872815281faaff06f496c3a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_native.h new file mode 100644 index 0000000000000000000000000000000000000000..945c54f82e559d0f85fb9549388a15e2e3137414 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_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 _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 native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fc44f65860f09d2861448b9929070abeb8bcae96 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_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 _cslt_sparse_mm_search { + using schema = int64_t (const at::Tensor &, const at::Tensor &, const ::std::optional &, 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::_cslt_sparse_mm_search"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int"; + static int64_t call(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..0792fa506bf44ca3e710ce2eb0fbb43ccbabea8b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss.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::_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) +inline ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false) { + return at::_ops::_ctc_loss::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); +} + +// aten::_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) +inline ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false) { + return at::_ops::_ctc_loss_Tensor::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); +} + +// aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::_ctc_loss_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} +// aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::_ctc_loss_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} + +// aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::_ctc_loss_Tensor_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); +} +// aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::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) { + return at::_ops::_ctc_loss_Tensor_out::call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..9cad37c224e253e8075474f5f0b14053b0744c88 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward.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::_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor +inline at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false) { + return at::_ops::_ctc_loss_backward::call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); +} + +// aten::_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor +inline at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false) { + return at::_ops::_ctc_loss_backward_Tensor::call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); +} + +// aten::_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _ctc_loss_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false) { + return at::_ops::_ctc_loss_backward_out::call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity, out); +} +// aten::_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _ctc_loss_backward_outf(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out) { + return at::_ops::_ctc_loss_backward_out::call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..885641dbb21a9489eda9adf1bebb324027e3fdb3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _ctc_loss_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor & _ctc_loss_backward_outf(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..247dd29836de80b77b780d31022f4035bb80ea3b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_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 _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..68582133f49f3da313eba130242186bb05ae61c8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b2e6708dedfd9a0117cfa3009d8f34e74696cddb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_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 & _ctc_loss_backward_out(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); +TORCH_API at::Tensor ctc_loss_backward_cpu(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor ctc_loss_backward_gpu(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor ctc_loss_backward_tensor(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b6080fa9f7906aea5e1a8d8f002aacc742aa45e3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _ctc_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_backward_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss_backward"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d661df33586ce795b00902dbc115183f6565903a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ab5f11ba794852d76669a09d59e607455cc3cbe --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6afac726b83665c3ad160d6c04a019d6e63fa5bd --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_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 _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_meta_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8760eac21dc6e051260a2aee8ad0cc79bdb713ff --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_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 ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d2c44f71d07d21b5e84b23ce7b8615c3e0cb4b7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _ctc_loss_out(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple ctc_loss_cpu(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple ctc_loss_gpu(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple ctc_loss_meta(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); +TORCH_API ::std::tuple _ctc_loss_Tensor_out(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple ctc_loss_tensor(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, bool zero_infinity=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b4ecd806780ffe27269f9cff20ac79895290c097 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _ctc_loss { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_Tensor { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity); +}; + +struct TORCH_API _ctc_loss_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +}; + +struct TORCH_API _ctc_loss_Tensor_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_ctc_loss"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..32a840c3ade52511764cc1b45d4630d494d30be5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_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::_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) +inline ::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) { + return at::_ops::_cudnn_attention_backward::call(grad_out, query, key, value, out, logsumexp, philox_seed, philox_offset, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, scale); +} +namespace symint { + template >> + ::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) { + return at::_ops::_cudnn_attention_backward::call(grad_out, query, key, value, out, logsumexp, philox_seed, philox_offset, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, scale); + } +} + +// aten::_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) +inline ::std::tuple _cudnn_attention_backward_symint(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=::std::nullopt) { + return at::_ops::_cudnn_attention_backward::call(grad_out, query, key, value, out, logsumexp, philox_seed, philox_offset, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, scale); +} +namespace symint { + template >> + ::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, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_backward::call(grad_out, query, key, value, out, logsumexp, philox_seed, philox_offset, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bcd5a185efa5a564282867d4040ae8f2c3eada3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_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 _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); +TORCH_API ::std::tuple _cudnn_attention_backward_symint(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=::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6b04819a754858d9ec423c09c79abd0ab5933753 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1e39055877b285bf32c755f8c0e47deef209722 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..81260a2333292da71ddbec1ca352a055be3f730f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cudnn_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask) +inline ::std::tuple _cudnn_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); +} +namespace symint { + template >> + ::std::tuple _cudnn_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); + } +} + +// aten::_cudnn_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask) +inline ::std::tuple _cudnn_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); +} +namespace symint { + template >> + ::std::tuple _cudnn_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_cudnn_attention_forward::call(query, key, value, attn_bias, cum_seq_q, cum_seq_k, max_q, max_k, compute_log_sumexp, dropout_p, is_causal, return_debug_mask, scale); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c63ea70606899e95322eee59168e49b9e63e8da4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f36bf874f40467b62e656ec893455a46bfec9c39 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c9203fd2ac03e45ec624145787c3ef99b25da52 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_attention_forward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cudnn_attention_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, bool, double, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_attention_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cudnn_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask)"; + static ::std::tuple call(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, bool is_causal, bool return_debug_mask, ::std::optional scale); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_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, bool is_causal, bool return_debug_mask, ::std::optional scale); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..ee9ca2bae229a4baf6a0529401fd079bfd5db686 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss.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::_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) +inline ::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) { + return at::_ops::_cudnn_ctc_loss::call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity); +} + +// aten::_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) +inline ::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) { + return at::_ops::_cudnn_ctc_loss_Tensor::call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity); +} + +// aten::_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _cudnn_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, bool deterministic, bool zero_infinity) { + return at::_ops::_cudnn_ctc_loss_out::call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity, out0, out1); +} +// aten::_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _cudnn_ctc_loss_outf(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, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_cudnn_ctc_loss_out::call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bc60cd4fc6be380297408805233b6bd5b7b640b7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_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 _cudnn_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, bool deterministic, bool zero_infinity); +TORCH_API ::std::tuple _cudnn_ctc_loss_outf(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, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ccb9bd5069ad0a5e1b2281050771f139447ad78 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..097f66e6b653f7fc0c33a491cad2c2067b7a532f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _cudnn_ctc_loss_out(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, at::Tensor & out0, at::Tensor & out1); +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_tensor(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 native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80219580c7f35528cb79e40c2eb6492d98ae9ba2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_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 _cudnn_ctc_loss { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, int64_t, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_ctc_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity); +}; + +struct TORCH_API _cudnn_ctc_loss_Tensor { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_ctc_loss"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool deterministic, bool zero_infinity); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool deterministic, bool zero_infinity); +}; + +struct TORCH_API _cudnn_ctc_loss_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, 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::_cudnn_ctc_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state.h new file mode 100644 index 0000000000000000000000000000000000000000..4ac592051664f5e384e05d5ccedabdd32f7e9703 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state.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::_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, at::TensorOptions options) { + return at::_ops::_cudnn_init_dropout_state::call(dropout, train, dropout_seed, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_cudnn_init_dropout_state::call(dropout, train, dropout_seed, dtype, layout, device, pin_memory); +} + +// aten::_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_init_dropout_state_out(at::Tensor & out, double dropout, bool train, int64_t dropout_seed) { + return at::_ops::_cudnn_init_dropout_state_out::call(dropout, train, dropout_seed, out); +} +// aten::_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_init_dropout_state_outf(double dropout, bool train, int64_t dropout_seed, at::Tensor & out) { + return at::_ops::_cudnn_init_dropout_state_out::call(dropout, train, dropout_seed, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f8d410d77e4bff3e29e0268f9444eebd0e8da1f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _cudnn_init_dropout_state_out(at::Tensor & out, double dropout, bool train, int64_t dropout_seed); +TORCH_API at::Tensor & _cudnn_init_dropout_state_outf(double dropout, bool train, int64_t dropout_seed, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5a503d65ba1d2eaa098f002ed0799b29e6f42647 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, at::TensorOptions options); +TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_native.h new file mode 100644 index 0000000000000000000000000000000000000000..710bb07a3fdc9d3d6f4cea4ef02af89b9ae67ab2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_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 & _cudnn_init_dropout_state_out(double dropout, bool train, int64_t dropout_seed, at::Tensor & out); +TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bf36a0b5a2f2814e08362e3f829438df8fd4bb86 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cudnn_init_dropout_state { + using schema = at::Tensor (double, bool, 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::_cudnn_init_dropout_state"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor"; + static at::Tensor call(double dropout, bool train, int64_t dropout_seed, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, double dropout, bool train, int64_t dropout_seed, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API _cudnn_init_dropout_state_out { + using schema = at::Tensor & (double, bool, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_init_dropout_state"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(double dropout, bool train, int64_t dropout_seed, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, double dropout, bool train, int64_t dropout_seed, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn.h new file mode 100644 index 0000000000000000000000000000000000000000..1290445673496c49e04d2f5adeacb29670442e32 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state); + } +} + +// aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _cudnn_rnn_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, out0, out1, out2, out3, out4); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); + } +} + +// aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _cudnn_rnn_symint_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); +} +namespace symint { + template >> + ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_cudnn_rnn_out::call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..d9729fdb79f7f1b7dbb8fd1ceb54a6ef4670f501 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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::_cudnn_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) +inline ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, reserve, output_mask); +} +namespace symint { + template >> + ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, reserve, output_mask); + } +} + +// aten::_cudnn_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) +inline ::std::tuple> _cudnn_rnn_backward_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); +} +namespace symint { + template >> + ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); + } +} + +// aten::_cudnn_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void _cudnn_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +namespace symint { + template >> + void _cudnn_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, reserve, output_mask, out0, out1, out2, out3); + } +} + +// aten::_cudnn_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void _cudnn_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +namespace symint { + template >> + void _cudnn_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, c10::fromIntArrayRefSlow(batch_sizes), dropout_state, reserve, output_mask, out0, out1, out2, out3); + } +} + +// aten::_cudnn_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void _cudnn_rnn_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +namespace symint { + template >> + void _cudnn_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); + } +} + +// aten::_cudnn_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void _cudnn_rnn_backward_symint_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +namespace symint { + template >> + void _cudnn_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::_cudnn_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..09273f58f97986da8d108e1846a85fa193311e15 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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 void _cudnn_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API void _cudnn_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +TORCH_API void _cudnn_rnn_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API void _cudnn_rnn_backward_symint_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d5bf5778afb93e82e9781edb211fbe43f939f84e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API ::std::tuple> _cudnn_rnn_backward_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..acbc753a92a4c8a546300f260dcafdbc0ddb63b0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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 void _cudnn_rnn_backward_out_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +TORCH_API ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f3f72a9cfeb939e3146eeae7743187bbb1d1b164 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cudnn_rnn_backward { + using schema = ::std::tuple> (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const ::std::optional &, const at::Tensor &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_rnn_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cudnn_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[])"; + static ::std::tuple> call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); + static ::std::tuple> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +}; + +struct TORCH_API _cudnn_rnn_backward_out { + using schema = void (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const ::std::optional &, const at::Tensor &, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_rnn_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_cudnn_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> ()"; + static void call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..705217e301dc8bd8dbc2a78798bd8d7715219acb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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 _cudnn_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +TORCH_API ::std::tuple _cudnn_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +TORCH_API ::std::tuple _cudnn_rnn_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state); +TORCH_API ::std::tuple _cudnn_rnn_symint_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c4104e19fa10106a5b8fd0383caf20935ce0959b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +TORCH_API ::std::tuple _cudnn_rnn_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..5c0d8574d7d334de38eadbf24aeac146e0d06151 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cudnn_rnn_flatten_weight(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional) -> Tensor +inline at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); +} +namespace symint { + template >> + at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); + } +} + +// aten::_cudnn_rnn_flatten_weight(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional) -> Tensor +inline at::Tensor _cudnn_rnn_flatten_weight_symint(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); +} +namespace symint { + template >> + at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_symint_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_symint_outf(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3621007d9fc69a52c88df8177fba5447a59082d2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_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 & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +TORCH_API at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out); +TORCH_API at::Tensor & _cudnn_rnn_flatten_weight_symint_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +TORCH_API at::Tensor & _cudnn_rnn_flatten_weight_symint_outf(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e6c58f1553534ed23f7a77d0f56e75021f4e0fe --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_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_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +TORCH_API at::Tensor _cudnn_rnn_flatten_weight_symint(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6da6d455df11a7a93630e41b141070f9b56c4554 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_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 & _cudnn_rnn_flatten_weight_out_symint(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out); +TORCH_API at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..09c6961921bfc23c2a301eb838193d80afe39974 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_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 _cudnn_rnn_flatten_weight { + using schema = at::Tensor (at::TensorList, int64_t, c10::SymInt, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_rnn_flatten_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cudnn_rnn_flatten_weight(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional) -> Tensor"; + static at::Tensor call(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +}; + +struct TORCH_API _cudnn_rnn_flatten_weight_out { + using schema = at::Tensor & (at::TensorList, int64_t, c10::SymInt, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_rnn_flatten_weight"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02dfab48736c65ed86ffae0c42b4bf71fbf89f0a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _cudnn_rnn_out_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +TORCH_API ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..45f442955097aee3bff265b9cfa4bd2d27157a24 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cudnn_rnn { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const ::std::optional &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_rnn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state); +}; + +struct TORCH_API _cudnn_rnn_out { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const ::std::optional &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const ::std::optional &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cudnn_rnn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))"; + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h new file mode 100644 index 0000000000000000000000000000000000000000..928d26c6067cd351fc281e00b948ded3f085c5e5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_clear_plan_cache(DeviceIndex device_index) -> () +inline void _cufft_clear_plan_cache(at::DeviceIndex device_index) { + return at::_ops::_cufft_clear_plan_cache::call(device_index); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e7c95905caa3e9c1c2131306d1ac9223dbaff93e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eeabd82eab4c8ecac04b7fa181d6a5fcecbec03e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_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 _cufft_clear_plan_cache(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..355a8692d7982c85776e9642796f23a8a9b9c30d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size.h new file mode 100644 index 0000000000000000000000000000000000000000..a52157f65be2298de1d1c76e35533c9d7415c904 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_get_plan_cache_max_size(DeviceIndex device_index) -> int +inline int64_t _cufft_get_plan_cache_max_size(at::DeviceIndex device_index) { + return at::_ops::_cufft_get_plan_cache_max_size::call(device_index); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..76bab16b1c9e653e9a64ef5b573233e41f52988a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_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 int64_t _cufft_get_plan_cache_max_size(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b00f1ed7629e09dbccc03b28f3cb1e2443fe3409 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..54666932c42fe9d160a174a89644a0a2600c28dd --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cufft_get_plan_cache_max_size { + using schema = int64_t (at::DeviceIndex); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cufft_get_plan_cache_max_size"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cufft_get_plan_cache_max_size(DeviceIndex device_index) -> int"; + static int64_t call(at::DeviceIndex device_index); + static int64_t 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size.h new file mode 100644 index 0000000000000000000000000000000000000000..aa988b125eb6561e593eb3dd08c68eae48a18d52 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_get_plan_cache_size(DeviceIndex device_index) -> int +inline int64_t _cufft_get_plan_cache_size(at::DeviceIndex device_index) { + return at::_ops::_cufft_get_plan_cache_size::call(device_index); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..864e229f3059c64d5b977af80c3a93c96a7e75c2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_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 int64_t _cufft_get_plan_cache_size(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0af2cc65777a61984cfeafd36cb7545cac3e26e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_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_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..977592d6b3143731b04b2d677d902da8f5113743 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cufft_get_plan_cache_size { + using schema = int64_t (at::DeviceIndex); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cufft_get_plan_cache_size"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cufft_get_plan_cache_size(DeviceIndex device_index) -> int"; + static int64_t call(at::DeviceIndex device_index); + static int64_t 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size.h new file mode 100644 index 0000000000000000000000000000000000000000..70a7131dc202ebe5c1e8e57359081b2f7f74230e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_set_plan_cache_max_size(DeviceIndex device_index, int max_size) -> () +inline void _cufft_set_plan_cache_max_size(at::DeviceIndex device_index, int64_t max_size) { + return at::_ops::_cufft_set_plan_cache_max_size::call(device_index, max_size); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..925e7d0a00803c73aa2fb40eb3f62e3acc13fc89 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_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 void _cufft_set_plan_cache_max_size(at::DeviceIndex device_index, int64_t max_size); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f6ee55fed1e11d954990ef9ea0e41961d6c6a4e4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_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 void _cufft_set_plan_cache_max_size(at::DeviceIndex device_index, int64_t max_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4e0611d4a06aaae76bceeb999428454275edd85b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_set_plan_cache_max_size_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cufft_set_plan_cache_max_size { + using schema = void (at::DeviceIndex, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cufft_set_plan_cache_max_size"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cufft_set_plan_cache_max_size(DeviceIndex device_index, int max_size) -> ()"; + static void call(at::DeviceIndex device_index, int64_t max_size); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::DeviceIndex device_index, int64_t max_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..9508d14d0a9ded2f6440a936b5b95f8f4236ded3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_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::_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> () +inline void _cummax_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim) { + return at::_ops::_cummax_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa685ddabfedfd6f7a391d0e7da066c5565cd60c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API void _cummax_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..202ca9740cceaae69b64695043633ba920cbfeb3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _cummax_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_native.h new file mode 100644 index 0000000000000000000000000000000000000000..05323e563a17883f6cb2d0f9500b6cf52b9501b4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b3a85ee2828cf2e40d61d9d954ee98376ffbe1f9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummax_helper_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 _cummax_helper { + using schema = void (const at::Tensor &, 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::_cummax_helper"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> ()"; + static void call(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..d231bc46d39943fe9f7aa697d8f8375dac510018 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..002ec7e4196375c534238a9124da0bf2fc8de6f3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a0e776f5b0e4a5f001bdf36e7e5bdc5d50f12af --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _cummin_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c9c59dc1f3bdab3c119045d162e235e21cd34c90 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void cummin_helper_cpu(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +TORCH_API void cummin_helper_cuda(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2d5dfe334f95424b10a8197859cb5fa6552df389 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_cummin_helper_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 _cummin_helper { + using schema = void (const at::Tensor &, 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::_cummin_helper"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cummin_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> ()"; + static void call(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap.h new file mode 100644 index 0000000000000000000000000000000000000000..73f8cacf914ae011dd2fadac3dcfc5b53964b749 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap.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::_debug_has_internal_overlap(Tensor self) -> int +inline int64_t _debug_has_internal_overlap(const at::Tensor & self) { + return at::_ops::_debug_has_internal_overlap::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c438b64ce7aca7a6a231b50468e1cea1b8d8150 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_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 int64_t _debug_has_internal_overlap(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_native.h new file mode 100644 index 0000000000000000000000000000000000000000..76dea456fef7f63585533adaf483ad20dbd50aac --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_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 _debug_has_internal_overlap(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..984a0d5072a750908230258c7b29e0af0b65d68e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_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 _debug_has_internal_overlap { + using schema = int64_t (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_debug_has_internal_overlap"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_debug_has_internal_overlap(Tensor self) -> int"; + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI.h new file mode 100644 index 0000000000000000000000000000000000000000..ba1548622df0a7d3931a412306db032a82eacc6f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4b471508f6f2a84a85fbebad8177f837c4aaa808 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI_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 sparse_dim_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e1864bed0f2c1ed5bb5fb8e2b2c5ac82649ddfea --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimI_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 _dimI { + using schema = int64_t (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_dimI"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dimI(Tensor self) -> int"; + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV.h new file mode 100644 index 0000000000000000000000000000000000000000..d2e3359194e74052bd7c68d8c0646df2bfd20112 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7f9c3e233b05882dfc85696d53fbb2cb46735c49 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV_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 dense_dim_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..faaff9c8bbeafbef6053f1d0232112434d556cf4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dimV_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 _dimV { + using schema = int64_t (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_dimV"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dimV(Tensor self) -> int"; + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange.h new file mode 100644 index 0000000000000000000000000000000000000000..75c830015d3fe59e12256c6ff50dbede1ba9298c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange.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::_dim_arange(Tensor like, int dim) -> Tensor +inline at::Tensor _dim_arange(const at::Tensor & like, int64_t dim) { + return at::_ops::_dim_arange::call(like, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d94aacd6395a1d355d4f531941ef5139198d4080 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_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 _dim_arange(const at::Tensor & like, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_native.h new file mode 100644 index 0000000000000000000000000000000000000000..750be6da9ef6f51708145a511fdc1bef90823ec3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _dim_arange(const at::Tensor & like, int64_t dim); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4820d88fc39c245779c10665f4c4bc72d11f4486 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dim_arange_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 _dim_arange { + 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::_dim_arange"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dim_arange(Tensor like, int dim) -> Tensor"; + static at::Tensor call(const at::Tensor & like, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & like, int64_t dim); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad.h new file mode 100644 index 0000000000000000000000000000000000000000..79e94a580a96c18badb99633b0b740caec451b2f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad.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::_dirichlet_grad(Tensor x, Tensor alpha, Tensor total) -> Tensor +inline at::Tensor _dirichlet_grad(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total) { + return at::_ops::_dirichlet_grad::call(x, alpha, total); +} + +// aten::_dirichlet_grad.out(Tensor x, Tensor alpha, Tensor total, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _dirichlet_grad_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total) { + return at::_ops::_dirichlet_grad_out::call(x, alpha, total, out); +} +// aten::_dirichlet_grad.out(Tensor x, Tensor alpha, Tensor total, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _dirichlet_grad_outf(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, at::Tensor & out) { + return at::_ops::_dirichlet_grad_out::call(x, alpha, total, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3f8ecf117b54ad6e04b3f52857ea2a48e628e953 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..89d38a57a70f2e857f794f5113ebfc8b9d4ed51a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ca79352c2326048858db780c10a55853ef81bf3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..814b3bdc81eddc916e930d6baed8e3a4addd0fba --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_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 & _dirichlet_grad_out(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, at::Tensor & out); +TORCH_API at::Tensor _dirichlet_grad_cpu(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); +TORCH_API at::Tensor _dirichlet_grad_cuda(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..095ba4ce6a15fa24c2e15faadaa85528a7f7d10f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad_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 _dirichlet_grad { + 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::_dirichlet_grad"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dirichlet_grad(Tensor x, Tensor alpha, Tensor total) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); +}; + +struct TORCH_API _dirichlet_grad_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::_dirichlet_grad"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_dirichlet_grad.out(Tensor x, Tensor alpha, Tensor total, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit.h new file mode 100644 index 0000000000000000000000000000000000000000..243e406de3282d91f0c9b331aa4e188f2b9e4434 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit.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::_dyn_quant_matmul_4bit(Tensor inp, Tensor packed_weights, int block_size, int in_features, int out_features) -> Tensor +inline at::Tensor _dyn_quant_matmul_4bit(const at::Tensor & inp, const at::Tensor & packed_weights, int64_t block_size, int64_t in_features, int64_t out_features) { + return at::_ops::_dyn_quant_matmul_4bit::call(inp, packed_weights, block_size, in_features, out_features); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b0077774af5d0af67b9ecc5e40c335d1412002b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_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 _dyn_quant_matmul_4bit(const at::Tensor & inp, const at::Tensor & packed_weights, int64_t block_size, int64_t in_features, int64_t out_features); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..54a1dc563c8b19a87f495538ba6499ec3d6cb2d5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _dyn_quant_matmul_4bit_cpu(const at::Tensor & inp, const at::Tensor & packed_weights, int64_t block_size, int64_t in_features, int64_t out_features); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_matmul_4bit_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2a2f8d498fe7544ebf1a4a920c1200d693715199 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..05c883e7c4c7e948a418fe4a2c0044de02f3195f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_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::_dyn_quant_pack_4bit_weight(Tensor weights, Tensor scales_zeros, Tensor? bias, int block_size, int in_features, int out_features) -> Tensor +inline at::Tensor _dyn_quant_pack_4bit_weight(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) { + return at::_ops::_dyn_quant_pack_4bit_weight::call(weights, scales_zeros, bias, block_size, in_features, out_features); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..16588a6610e05dd3af70815b54a4fefe54ad0c26 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_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 _dyn_quant_pack_4bit_weight(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 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..90e3f677966f357a56cceaee15440251eaab82d1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_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 at::Tensor _dyn_quant_pack_4bit_weight_cpu(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 native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_dyn_quant_pack_4bit_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b66d8cf450c726c549cd65e1ed8e193338995e47 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..b49aac51258dd13a74274d0cda3c89a258dfa9ae --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff23210d320d2cfebecf9d9f785e402be9b818f7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_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 _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); +TORCH_API ::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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..74b3293e8b507c96e7b0598f0910ae073beaa1fa --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_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 _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); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..76e29937d82ea80ead9e28419d4d2b37b6572e1d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_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 _efficient_attention_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, const at::Tensor &, double, const at::Tensor &, const at::Tensor &, int64_t, bool, ::std::optional, ::std::optional, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_efficient_attention_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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)"; + static ::std::tuple call(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::optional num_splits_key, ::std::optional window_size, bool shared_storage_dqdkdv); + 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 ::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::optional num_splits_key, ::std::optional window_size, bool shared_storage_dqdkdv); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..3eb5dd507368b5f758b094759239fc56364aafa4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt? max_seqlen_q, SymInt? max_seqlen_k, float dropout_p, int custom_mask_type, bool compute_log_sumexp=False, *, float? scale=None, Tensor? seqlen_k=None, int? window_size=None) -> (Tensor output, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, SymInt max_seqlen_batch_q, SymInt max_seqlen_batch_k) +inline ::std::tuple _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_q)) : ::std::nullopt, max_seqlen_k.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_k)) : ::std::nullopt, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); +} +namespace symint { + template >> + ::std::tuple _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_q)) : ::std::nullopt, max_seqlen_k.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_k)) : ::std::nullopt, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); + } +} + +// aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt? max_seqlen_q, SymInt? max_seqlen_k, float dropout_p, int custom_mask_type, bool compute_log_sumexp=False, *, float? scale=None, Tensor? seqlen_k=None, int? window_size=None) -> (Tensor output, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, SymInt max_seqlen_batch_q, SymInt max_seqlen_batch_k) +inline ::std::tuple _efficient_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); +} +namespace symint { + template >> + ::std::tuple _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..deb026de9500501f0ec49c416a4cb0ab2ed70fd6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_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 _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt); +TORCH_API ::std::tuple _efficient_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8b9786361eb2dd0695526fb5e44932f40d00d782 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_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 _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8204e119dd383efff154ec7afcd11917626be689 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficient_attention_forward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _efficient_attention_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, ::std::optional, ::std::optional, double, int64_t, bool, ::std::optional, const ::std::optional &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_efficient_attention_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt? max_seqlen_q, SymInt? max_seqlen_k, float dropout_p, int custom_mask_type, bool compute_log_sumexp=False, *, float? scale=None, Tensor? seqlen_k=None, int? window_size=None) -> (Tensor output, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, SymInt max_seqlen_batch_q, SymInt max_seqlen_batch_k)"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp, ::std::optional scale, const ::std::optional & seqlen_k, ::std::optional window_size); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp, ::std::optional scale, const ::std::optional & seqlen_k, ::std::optional window_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor.h new file mode 100644 index 0000000000000000000000000000000000000000..270f7fc034daef2c68d32365c39de8a93311963c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor.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::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_efficientzerotensor::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor _efficientzerotensor(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_efficientzerotensor::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_efficientzerotensor::call(size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor _efficientzerotensor(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_efficientzerotensor::call(size, dtype, layout, device, pin_memory); + } +} + +// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _efficientzerotensor_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & _efficientzerotensor_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _efficientzerotensor_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & _efficientzerotensor_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _efficientzerotensor_symint_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::_efficientzerotensor_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & _efficientzerotensor_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::_efficientzerotensor_out::call(size, out); + } +} + +// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _efficientzerotensor_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::_efficientzerotensor_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & _efficientzerotensor_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::_efficientzerotensor_out::call(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..58fad5b1b2ff28a9c997fee57272d9ca89258453 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_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 & _efficientzerotensor_out(at::Tensor & out, at::IntArrayRef size); +TORCH_API at::Tensor & _efficientzerotensor_outf(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & _efficientzerotensor_symint_out(at::Tensor & out, c10::SymIntArrayRef size); +TORCH_API at::Tensor & _efficientzerotensor_symint_outf(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b99d0496e62c10d893ac1ef0c5b77a526a1ea5f9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_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 _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..38a3603d686962edc1f87b308c87edbe974a5661 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_meta_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..815bec1c6b8b5463322c58f27d8650c0c93b6235 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_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 _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0a007cbbe5018bcfe171da9f4c8acf0df4501cac --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..01ef25043726dd808096e74585b3c596ab01ce38 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_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 _efficientzerotensor { + 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::_efficientzerotensor"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_efficientzerotensor(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 _efficientzerotensor_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::_efficientzerotensor"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_efficientzerotensor.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); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag.h new file mode 100644 index 0000000000000000000000000000000000000000..5d43971fc97bad4a53c4cfb07f646b1c330d2896 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag.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::_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) +inline ::std::tuple _embedding_bag(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) { + return at::_ops::_embedding_bag::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx); +} + +// aten::_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!)) +inline ::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) { + return at::_ops::_embedding_bag_out::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); +} +// aten::_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!)) +inline ::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) { + return at::_ops::_embedding_bag_out::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..88a39f33471d10da6699a3e42af057255cb377df --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_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::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_backward::call(grad, indices, offsets, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, sparse, per_sample_weights, padding_idx); +} +namespace symint { + template >> + at::Tensor _embedding_bag_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_backward::call(grad, indices, offsets, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, sparse, per_sample_weights, padding_idx); + } +} + +// aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_backward::call(grad, indices, offsets, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, sparse, per_sample_weights, padding_idx); +} +namespace symint { + template >> + at::Tensor _embedding_bag_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_backward::call(grad, indices, offsets, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, sparse, per_sample_weights, padding_idx); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9544335046d776821fcdee82c30e04c3b8db08ab --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cd72c38c07bce68a6e4e0cc129338d3e56733a8d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3a3273c8d101d64f7006ad88ccd25aa7b6eada05 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _embedding_bag_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3403960e54211b3a33ab374b71ea1f948c8d865e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _embedding_bag_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, bool, int64_t, bool, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c970fc5115c0f8a2d2bdfa79fa325ef11501a990 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..165cd38c193cfbad6a3354f81203e07d769857d2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..71345fc5ab226c1c2bc1cb805cd29b7f304b0321 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..7c2541f982101aad537118295f41ac7d34a57a06 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_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::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_dense_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); +} +namespace symint { + template >> + at::Tensor _embedding_bag_dense_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); + } +} + +// aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_dense_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); +} +namespace symint { + template >> + at::Tensor _embedding_bag_dense_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); + } +} + +// aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _embedding_bag_dense_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); +} +namespace symint { + template >> + at::Tensor & _embedding_bag_dense_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); + } +} + +// aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _embedding_bag_dense_backward_outf(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); +} +namespace symint { + template >> + at::Tensor & _embedding_bag_dense_backward_outf(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); + } +} + +// aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _embedding_bag_dense_backward_symint_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); +} +namespace symint { + template >> + at::Tensor & _embedding_bag_dense_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); + } +} + +// aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _embedding_bag_dense_backward_symint_outf(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); +} +namespace symint { + template >> + at::Tensor & _embedding_bag_dense_backward_outf(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out) { + return at::_ops::_embedding_bag_dense_backward_out::call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..080dfad3fa465a9219a097b99b448859f611f13f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _embedding_bag_dense_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor & _embedding_bag_dense_backward_outf(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out); +TORCH_API at::Tensor & _embedding_bag_dense_backward_symint_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor & _embedding_bag_dense_backward_symint_outf(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aefb66ab79c3e91cf8c14fa6fb89b9fe0e53131a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_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 _embedding_bag_dense_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_dense_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa45be286924ec27f6ded114fd1aa684a9e72a59 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_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 _embedding_bag_dense_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_dense_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..87194197c342475c9d507301ff890c4cee2ecb0b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _embedding_bag_dense_backward_out_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out); +TORCH_API at::Tensor _embedding_bag_dense_backward_cpu(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_dense_backward_cuda(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..04099d7303e4a27d490cd64a1293de6175c3b334 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_dense_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 _embedding_bag_dense_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, bool, int64_t, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_dense_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx); +}; + +struct TORCH_API _embedding_bag_dense_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, bool, int64_t, const ::std::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_dense_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only.h new file mode 100644 index 0000000000000000000000000000000000000000..935ffcd0b63a8ae7ad378a7b97defbfc61cc80f5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only.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::_embedding_bag_forward_only(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) +inline ::std::tuple _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_forward_only::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx); +} + +// aten::_embedding_bag_forward_only.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!)) +inline ::std::tuple _embedding_bag_forward_only_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) { + return at::_ops::_embedding_bag_forward_only_out::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); +} +// aten::_embedding_bag_forward_only.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!)) +inline ::std::tuple _embedding_bag_forward_only_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) { + return at::_ops::_embedding_bag_forward_only_out::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d74307ee632e81fcbe5efb98546dc71bac2d4469 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_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_forward_only_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_forward_only_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5621951a866b742829dc74abb60c99fc367d5c66 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_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 _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e854066f4967c44c831a937c816479d40a8926d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5eefe22fd8cc7395d7bd5261d869f9f2d3ccb097 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _embedding_bag_forward_only_out(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple _embedding_bag_forward_only_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +TORCH_API ::std::tuple _embedding_bag_forward_only_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5bc3634b973850a7ba338f9efb272f15e1acdd27 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_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_forward_only { + 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_forward_only"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag_forward_only(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_forward_only_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_forward_only"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_embedding_bag_forward_only.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f4265bc61c1451282f2ebbeb62941afe3ed42cae --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _embedding_bag_out(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple _embedding_bag_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +TORCH_API ::std::tuple _embedding_bag_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3632a09dae71a07f71cdfb4ff4f072e4ccba08a6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..40c48c22253136e3e88e5f85ee3814c25321e936 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_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::_embedding_bag_per_sample_weights_backward(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_per_sample_weights_backward(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_per_sample_weights_backward::call(grad, weight, indices, offsets, offset2bag, mode, padding_idx); +} + +// aten::_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _embedding_bag_per_sample_weights_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_per_sample_weights_backward_out::call(grad, weight, indices, offsets, offset2bag, mode, padding_idx, out); +} +// aten::_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _embedding_bag_per_sample_weights_backward_outf(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out) { + return at::_ops::_embedding_bag_per_sample_weights_backward_out::call(grad, weight, indices, offsets, offset2bag, mode, padding_idx, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b24ce717374bcf9d99ab82248d6d9f47abe81796 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _embedding_bag_per_sample_weights_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); +TORCH_API at::Tensor & _embedding_bag_per_sample_weights_backward_outf(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..622c3bcd1187844e91caf7553a7d459be771c2e4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_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 _embedding_bag_per_sample_weights_backward(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd78590e835d0548ad9df3030e827c5a6428dfdb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..875564b98801ad2e644dcaf67ed368c73c33e120 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _embedding_bag_per_sample_weights_backward_out(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out); +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward_cpu(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward_cuda(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..28d039d2f58afd9abb40095aef9b7a33695712dc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_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 _embedding_bag_per_sample_weights_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_per_sample_weights_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag_per_sample_weights_backward(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx); +}; + +struct TORCH_API _embedding_bag_per_sample_weights_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_per_sample_weights_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..89e04000d8ec2609bcb37cc9c9bb7d4a9ba70123 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_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::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_sparse_backward::call(grad, indices, offsets, offset2bag, bag_size, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); +} +namespace symint { + template >> + at::Tensor _embedding_bag_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_sparse_backward::call(grad, indices, offsets, offset2bag, bag_size, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); + } +} + +// aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor +inline at::Tensor _embedding_bag_sparse_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_sparse_backward::call(grad, indices, offsets, offset2bag, bag_size, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); +} +namespace symint { + template >> + at::Tensor _embedding_bag_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag_sparse_backward::call(grad, indices, offsets, offset2bag, bag_size, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1ca17ea9befdd479bd66dea863bc488aa9e26fa0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _embedding_bag_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +TORCH_API at::Tensor _embedding_bag_sparse_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..58d3d3f6025067f8b56c4d6ac265e958ced10e5e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _embedding_bag_sparse_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..165f9aafe069cf7ef4b35be04d7ed7c2fb11c6b3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_sparse_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _embedding_bag_sparse_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, bool, int64_t, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_embedding_bag_sparse_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const ::std::optional & per_sample_weights, int64_t padding_idx); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h new file mode 100644 index 0000000000000000000000000000000000000000..e057b95ce6860292bb51526bcbb0d3bc2aad5016 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc39f79a0f193addf7987315bffbc92ef2c68e4e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ccf34294570c508adf08ce89aafae4ee7227e38 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_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 _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format); +TORCH_API 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); +TORCH_API 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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fdac4039218f036227f30964e210afeb524359f6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _empty_affine_quantized_out_symint(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor empty_affine_quantized_other_backends_stub(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a68afff8bd1c495d4e3f9ae82ad62ad4ab40d2b1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _empty_affine_quantized { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional, double, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_empty_affine_quantized"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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"; + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _empty_affine_quantized_out { + using schema = at::Tensor & (c10::SymIntArrayRef, double, 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::_empty_affine_quantized"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, double scale, int64_t zero_point, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized.h new file mode 100644 index 0000000000000000000000000000000000000000..467fa5350ada685f02f79b42ec92f6af625abf78 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_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_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::_empty_per_channel_affine_quantized::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::_empty_per_channel_affine_quantized::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::_empty_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_per_channel_affine_quantized_symint(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized::call(size, scales, zero_points, axis, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor _empty_per_channel_affine_quantized(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized::call(size, scales, zero_points, axis, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_per_channel_affine_quantized_symint(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::_empty_per_channel_affine_quantized::call(size, scales, zero_points, axis, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template >> + at::Tensor _empty_per_channel_affine_quantized(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format) { + return at::_ops::_empty_per_channel_affine_quantized::call(size, scales, zero_points, axis, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_per_channel_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_per_channel_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, memory_format, out); + } +} + +// aten::_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_per_channel_affine_quantized_outf(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_per_channel_affine_quantized_outf(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scales, zero_points, axis, memory_format, out); + } +} + +// aten::_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_per_channel_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(size, scales, zero_points, axis, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_per_channel_affine_quantized_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(size, scales, zero_points, axis, memory_format, out); + } +} + +// aten::_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_per_channel_affine_quantized_symint_outf(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(size, scales, zero_points, axis, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_per_channel_affine_quantized_outf(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_per_channel_affine_quantized_out::call(size, scales, zero_points, axis, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..038327f183f308a3fc1781e5006d802c2c1966c7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_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_per_channel_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor & _empty_per_channel_affine_quantized_outf(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor & _empty_per_channel_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor & _empty_per_channel_affine_quantized_symint_outf(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c77d37bf79fb98479b8a1e67d538d3887e8890e2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_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 _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +TORCH_API at::Tensor _empty_per_channel_affine_quantized_symint(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor _empty_per_channel_affine_quantized_symint(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f2a416942e6b8fd9997faa8ee21b39d776e24345 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _empty_per_channel_affine_quantized_out_symint(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor empty_per_channel_affine_quantized_other_backends_stub(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +TORCH_API at::Tensor empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=c10::MemoryFormat::Contiguous); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f0c4f971c2a252dd1cb3590b3791f96ab7ac6bad --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _empty_per_channel_affine_quantized { + using schema = at::Tensor (c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_empty_per_channel_affine_quantized"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_empty_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API _empty_per_channel_affine_quantized_out { + using schema = at::Tensor & (c10::SymIntArrayRef, const 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::_empty_per_channel_affine_quantized"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist.h new file mode 100644 index 0000000000000000000000000000000000000000..736ddb2122313cbc19aaaedf329d3456f3b3c1e7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist.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::_euclidean_dist(Tensor x1, Tensor x2) -> Tensor +inline at::Tensor _euclidean_dist(const at::Tensor & x1, const at::Tensor & x2) { + return at::_ops::_euclidean_dist::call(x1, x2); +} + +// aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _euclidean_dist_out(at::Tensor & out, const at::Tensor & x1, const at::Tensor & x2) { + return at::_ops::_euclidean_dist_out::call(x1, x2, out); +} +// aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _euclidean_dist_outf(const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out) { + return at::_ops::_euclidean_dist_out::call(x1, x2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ddf765d22f899df3a0adbfa3f92254a3997897f0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_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 _euclidean_dist(const at::Tensor & x1, const at::Tensor & x2); +TORCH_API at::Tensor & _euclidean_dist_out(at::Tensor & out, const at::Tensor & x1, const at::Tensor & x2); +TORCH_API at::Tensor & _euclidean_dist_outf(const at::Tensor & x1, const at::Tensor & x2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d35bdc772aa53366cbdc67cf0771640e3dcfe067 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_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 _euclidean_dist(const at::Tensor & x1, const at::Tensor & x2); +TORCH_API at::Tensor & _euclidean_dist_out(const at::Tensor & x1, const at::Tensor & x2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..251d460ef836cc36a1f27d3ab695f29c851f1071 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_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 _euclidean_dist { + 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::_euclidean_dist"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_euclidean_dist(Tensor x1, Tensor x2) -> Tensor"; + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2); +}; + +struct TORCH_API _euclidean_dist_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::_euclidean_dist"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine.h new file mode 100644 index 0000000000000000000000000000000000000000..33a2d5bb1bdc023ed97735a00d2a4f93e5ff0c05 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..03064ade4a22ffb017ac37ab696dceeab6f0aa57 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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::_fake_quantize_learnable_per_channel_affine_backward(Tensor grad, Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, 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_backward::call(grad, self, scale, zero_point, axis, quant_min, quant_max, grad_factor); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c6a523d2ac919c741f14c082beb6b5423e13c17f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, 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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..867d3fadab255b1fa15498850db4e0c00594e5ca --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, 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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..69ccbaca4b312d32f52d9549c0d3d1cb8efdc3cb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, 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); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..51ac5b1e3d19b4794af6e2ac8e34f3f37575f0fe --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _fake_quantize_learnable_per_channel_affine_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, 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_channel_affine_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fake_quantize_learnable_per_channel_affine_backward(Tensor grad, Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad, 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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, 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); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..81f7ff920c55ea5edd6edb2989515be6a8b9bf57 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 & _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); +TORCH_API 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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37f9e9c3fa100ea0294769939db57e6f35fee8c8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_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_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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..23eafc8f01bfb3bfb27056e7499b9244e394f4ad --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _fake_quantize_learnable_per_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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b65953332cc9e495f6957d81562d3acee7c34706 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 & _fake_quantize_learnable_per_channel_affine_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, at::Tensor & out); +TORCH_API 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); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dec0cb882832bae79669a73d6b2c98556f25ddcd --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_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_channel_affine { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, 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_channel_affine"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, 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 axis, int64_t quant_min, int64_t quant_max, double grad_factor); +}; + +struct TORCH_API _fake_quantize_learnable_per_channel_affine_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, 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_channel_affine"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_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!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, 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 axis, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine.h new file mode 100644 index 0000000000000000000000000000000000000000..877ad1e7b9548bbd01494854095a76ff1fcb4db6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_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_tensor_affine(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor +inline 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) { + return at::_ops::_fake_quantize_learnable_per_tensor_affine::call(self, scale, zero_point, quant_min, quant_max, grad_factor); +} + +// aten::_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!) +inline at::Tensor & _fake_quantize_learnable_per_tensor_affine_out(at::Tensor & out, 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) { + return at::_ops::_fake_quantize_learnable_per_tensor_affine_out::call(self, scale, zero_point, quant_min, quant_max, grad_factor, out); +} +// aten::_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!) +inline at::Tensor & _fake_quantize_learnable_per_tensor_affine_outf(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) { + return at::_ops::_fake_quantize_learnable_per_tensor_affine_out::call(self, scale, zero_point, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..ec64714d6b487a1d82ef7156a029968e7e990868 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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::_fake_quantize_learnable_per_tensor_affine_backward(Tensor grad, Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _fake_quantize_learnable_per_tensor_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0) { + return at::_ops::_fake_quantize_learnable_per_tensor_affine_backward::call(grad, self, scale, zero_point, quant_min, quant_max, grad_factor); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..338726346da75a6e6a425393958370614bf9e7a7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _fake_quantize_learnable_per_tensor_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6806a586c44e09b6e61773731c147f839c036cb9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _fake_quantize_learnable_per_tensor_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..23cf37ab766b548d415cb1618edf75a5c43a5b11 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _fake_quantize_learnable_per_tensor_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cab6c7286003308bd57bf8ed2eca743a05e7cdfd --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _fake_quantize_learnable_per_tensor_affine_backward { + using schema = ::std::tuple (const 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_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fake_quantize_learnable_per_tensor_affine_backward(Tensor grad, Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb4968bd5cf083e9fddcc36cf27572c4b32d2813 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 & _fake_quantize_learnable_per_tensor_affine_out(at::Tensor & out, 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); +TORCH_API at::Tensor & _fake_quantize_learnable_per_tensor_affine_outf(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 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5f8d830cc6360ae2df1a33090c87053820e06048 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _fake_quantize_learnable_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5e39605cb4cc6e62ba9e16866a62429f72eed1e7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 & _fake_quantize_learnable_per_tensor_affine_out(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); +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 native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f4198c299329cc9d6800a4cd2c57d0de94a16047 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.h new file mode 100644 index 0000000000000000000000000000000000000000..6c977130464c7c222120692846c68a4bb1784767 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.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_tensor_affine_cachemask_tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max) -> (Tensor output, Tensor mask) +inline ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max) { + return at::_ops::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams::call(self, scale, zero_point, fake_quant_enabled, quant_min, quant_max); +} + +// aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max) { + return at::_ops::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::call(self, scale, zero_point, fake_quant_enabled, quant_min, quant_max, out0, out1); +} +// aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::call(self, scale, zero_point, fake_quant_enabled, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c3628eba21df00a00f70986da53533550973638 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_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_tensor_qparams_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); +TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2824af81e46863d4d3529011f5ed20ab9bc8a603 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..07bcaea1533c3709d7e977f945b9926e7fc730d0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_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_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_native.h new file mode 100644 index 0000000000000000000000000000000000000000..17f921e81c38c566083120f0d6df285f2f72730a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_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 _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7678af17f9eea0d745daf7dac08515f5534e1874 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_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_per_tensor_affine_cachemask_tensor_qparams { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fake_quantize_per_tensor_affine_cachemask_tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max) -> (Tensor output, Tensor mask)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); +}; + +struct TORCH_API _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c.h new file mode 100644 index 0000000000000000000000000000000000000000..25c47dd14878a472dfc2d7aed454025d9c982481 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor +inline at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward); +} +namespace symint { + template >> + at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward); + } +} + +// aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor +inline at::Tensor _fft_c2c_symint(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, dim, normalization, forward); +} +namespace symint { + template >> + at::Tensor _fft_c2c(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, dim, normalization, forward); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_symint_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2c_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d2115217f279267a31eec4099b42ef5e40cba30e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_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 _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 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5663179fad82d3153a9a609db01eaf988c650d6b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_native.h new file mode 100644 index 0000000000000000000000000000000000000000..866253752563c7ae2955a73e71d7f9e0ae3995c1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_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 _fft_c2c_mkl(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_mkl_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); +TORCH_API at::Tensor _fft_c2c_cufft(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_cufft_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0a1e3c720c5c3956b06aaa4d02c81cb3dcb2b45c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2c_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_c2c { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_c2c"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward); +}; + +struct TORCH_API _fft_c2c_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_c2c"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h new file mode 100644 index 0000000000000000000000000000000000000000..05de31e8a7e740eb156213087a4446a8ce4600f8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template >> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template >> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template >> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e7dfef5dc11c85c80f8c590621134fbfed3abe6c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_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 _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); +TORCH_API at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size); +TORCH_API at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); +TORCH_API at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out); +TORCH_API at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size); +TORCH_API at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70b8e510104338a9b3d772aff77066d0be99d200 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_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_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); +TORCH_API at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size); +TORCH_API at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); +TORCH_API at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out); +TORCH_API at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size); +TORCH_API at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8843e05d4d623c7b1f1ca5deff2f7f1a152dc8f3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_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 _fft_c2r_mkl(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); +TORCH_API at::Tensor & _fft_c2r_mkl_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out); +TORCH_API at::Tensor _fft_c2r_cufft(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); +TORCH_API at::Tensor & _fft_c2r_cufft_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bbd8fd6ddd564c417188fd04b02493bd8f51a498 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r_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_c2r { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_c2r"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size); +}; + +struct TORCH_API _fft_c2r_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, int64_t, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_c2r"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c.h new file mode 100644 index 0000000000000000000000000000000000000000..7e98b167bc79b7932343df69c19388fed8fe5511 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c.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::_fft_r2c(Tensor self, int[] dim, int normalization, bool onesided) -> Tensor +inline at::Tensor _fft_r2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided) { + return at::_ops::_fft_r2c::call(self, dim, normalization, onesided); +} + +// aten::_fft_r2c.out(Tensor self, int[] dim, int normalization, bool onesided, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_r2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided) { + return at::_ops::_fft_r2c_out::call(self, dim, normalization, onesided, out); +} +// aten::_fft_r2c.out(Tensor self, int[] dim, int normalization, bool onesided, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_r2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out) { + return at::_ops::_fft_r2c_out::call(self, dim, normalization, onesided, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd215438571c9ecf1de81a8f0744625c73fa26e0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_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 _fft_r2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +TORCH_API at::Tensor & _fft_r2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +TORCH_API at::Tensor & _fft_r2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..913800e09b6a477c5eeaff2764eaeb326957ae82 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_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 _fft_r2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +TORCH_API at::Tensor & _fft_r2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +TORCH_API at::Tensor & _fft_r2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c2b923c93a2e2f244c43bc5ab1c6cfb046fafad --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_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 _fft_r2c_mkl(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +TORCH_API at::Tensor & _fft_r2c_mkl_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out); +TORCH_API at::Tensor _fft_r2c_cufft(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +TORCH_API at::Tensor & _fft_r2c_cufft_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80ca9c4276dd8ddb545a314ffa58883ff727e74a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fft_r2c { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_r2c"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fft_r2c(Tensor self, int[] dim, int normalization, bool onesided) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); +}; + +struct TORCH_API _fft_r2c_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_r2c"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fft_r2c.out(Tensor self, int[] dim, int normalization, bool onesided, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask.h new file mode 100644 index 0000000000000000000000000000000000000000..bf64a98d9151ce47adca5852703374f2ab0012e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask.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::_fill_mem_eff_dropout_mask_(Tensor(a!) self, float dropout_p, int seed, int offset) -> Tensor(a!) +inline at::Tensor & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset) { + return at::_ops::_fill_mem_eff_dropout_mask_::call(self, dropout_p, seed, offset); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..19b6a03275f8434753af7f2bf6c6bfe12ec32fb6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_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 & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_meta_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8815cf4a5ff02cb3ea7c31d6e1883250b0e86480 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_meta_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6553b50ffc4687cba57a062b8cb0a0dfd1d109fe --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8c623f0bb4291adcf6a4917406b598a28782e45f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_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 _fill_mem_eff_dropout_mask_ { + using schema = at::Tensor & (at::Tensor &, double, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fill_mem_eff_dropout_mask_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fill_mem_eff_dropout_mask_(Tensor(a!) self, float dropout_p, int seed, int offset) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double dropout_p, int64_t seed, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..3f302ef4d3f695a88175a4a0c4f3c29fbba5d496 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_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::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor rng_state, Tensor unused, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _flash_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 & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, rng_state, unused, scale, window_size_left.has_value() ? ::std::make_optional(c10::SymInt(*window_size_left)) : ::std::nullopt, window_size_right.has_value() ? ::std::make_optional(c10::SymInt(*window_size_right)) : ::std::nullopt); +} +namespace symint { + template >> + ::std::tuple _flash_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 & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, rng_state, unused, scale, window_size_left.has_value() ? ::std::make_optional(c10::SymInt(*window_size_left)) : ::std::nullopt, window_size_right.has_value() ? ::std::make_optional(c10::SymInt(*window_size_right)) : ::std::nullopt); + } +} + +// aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor rng_state, Tensor unused, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _flash_attention_backward_symint(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, rng_state, unused, scale, window_size_left, window_size_right); +} +namespace symint { + template >> + ::std::tuple _flash_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 & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, rng_state, unused, scale, window_size_left, window_size_right); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2acccc59813eb408fdd3b8795ff6d448b163ab76 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_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 _flash_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 & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt); +TORCH_API ::std::tuple _flash_attention_backward_symint(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c03cb9417b19063080a475116448906c3d39ad11 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_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 _flash_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 & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f22d632677fa3f0d81525698dd125f803c7b859a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _flash_attention_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymInt, double, bool, const at::Tensor &, const at::Tensor &, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_flash_attention_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor rng_state, Tensor unused, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & rng_state, const at::Tensor & unused, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..0832303503a3c17ee8ac260d5a34a985c4774a71 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, bool return_debug_mask, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None, Tensor? seqused_k=None, Tensor? alibi_slopes=None) -> (Tensor output, Tensor softmax_logsumexp, Tensor rng_state, Tensor unused, Tensor debug_attn_mask) +inline ::std::tuple _flash_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}) { + return at::_ops::_flash_attention_forward::call(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask, scale, window_size_left.has_value() ? ::std::make_optional(c10::SymInt(*window_size_left)) : ::std::nullopt, window_size_right.has_value() ? ::std::make_optional(c10::SymInt(*window_size_right)) : ::std::nullopt, seqused_k, alibi_slopes); +} +namespace symint { + template >> + ::std::tuple _flash_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}) { + return at::_ops::_flash_attention_forward::call(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask, scale, window_size_left.has_value() ? ::std::make_optional(c10::SymInt(*window_size_left)) : ::std::nullopt, window_size_right.has_value() ? ::std::make_optional(c10::SymInt(*window_size_right)) : ::std::nullopt, seqused_k, alibi_slopes); + } +} + +// aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, bool return_debug_mask, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None, Tensor? seqused_k=None, Tensor? alibi_slopes=None) -> (Tensor output, Tensor softmax_logsumexp, Tensor rng_state, Tensor unused, Tensor debug_attn_mask) +inline ::std::tuple _flash_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}) { + return at::_ops::_flash_attention_forward::call(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask, scale, window_size_left, window_size_right, seqused_k, alibi_slopes); +} +namespace symint { + template >> + ::std::tuple _flash_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}) { + return at::_ops::_flash_attention_forward::call(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask, scale, window_size_left, window_size_right, seqused_k, alibi_slopes); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..80a1b608071503760fb66dfb9787ddb5311c003c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_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 _flash_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}); +TORCH_API ::std::tuple _flash_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02e77d83510a2bb684b32b4a965f3b9db5f1c98b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_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 _flash_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt, const ::std::optional & seqused_k={}, const ::std::optional & alibi_slopes={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4f62a900123112922c4c4437bf17f15ff7f06428 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _flash_attention_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, double, bool, bool, ::std::optional, ::std::optional, ::std::optional, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_flash_attention_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, bool return_debug_mask, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None, Tensor? seqused_k=None, Tensor? alibi_slopes=None) -> (Tensor output, Tensor softmax_logsumexp, Tensor rng_state, Tensor unused, Tensor debug_attn_mask)"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right, const ::std::optional & seqused_k, const ::std::optional & alibi_slopes); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right, const ::std::optional & seqused_k, const ::std::optional & alibi_slopes); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar.h new file mode 100644 index 0000000000000000000000000000000000000000..fc22902fdac65e6b1c32deb88c0fa5931fa82908 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ca8f0c1739f3c39cff2c3f4387bed98c589faf5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_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 & _foobar_out(at::Tensor & out, const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=true); +TORCH_API at::Tensor & _foobar_outf(const at::Tensor & self, bool arg1, bool arg2, bool arg3, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a9d88faa9b705beec4a478c29c836c8e5ba48d3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_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 _foobar(const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5fec807e88ddbb0b427ca5fef4a20a075d418e63 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_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 & _foobar_out(const at::Tensor & self, bool arg1, bool arg2, bool arg3, at::Tensor & out); +TORCH_API at::Tensor foobar(const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fd38b948c4d120dc1e5c7c66598ee66ff33b8716 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar_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 _foobar { + using schema = at::Tensor (const at::Tensor &, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foobar"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool arg1, bool arg2, bool arg3); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool arg1, bool arg2, bool arg3); +}; + +struct TORCH_API _foobar_out { + using schema = at::Tensor & (const at::Tensor &, bool, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foobar"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, bool arg1, bool arg2, bool arg3, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool arg1, bool arg2, bool arg3, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs.h new file mode 100644 index 0000000000000000000000000000000000000000..47400324a259c4ab57e70eef89bb29abfbb2202c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs.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_abs(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_abs(at::TensorList self) { + return at::_ops::_foreach_abs::call(self); +} + +// aten::_foreach_abs_(Tensor(a!)[] self) -> () +inline void _foreach_abs_(at::TensorList self) { + return at::_ops::_foreach_abs_::call(self); +} + +// aten::_foreach_abs.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_abs_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_abs_out::call(self, out); +} +// aten::_foreach_abs.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_abs_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_abs_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a02d7692dc25890631d75f644f0c61065b4c5b8f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_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_abs(at::TensorList self); +TORCH_API void _foreach_abs_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_abs_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_abs_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ffd8acfb086f8b3ddec204204ad8a543d8cde58f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_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_abs(at::TensorList self); +TORCH_API void _foreach_abs_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5b5dc827b850733a98a5b3a6171f930ccb58f61d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_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_abs_slow(at::TensorList self); +TORCH_API void _foreach_abs_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_abs_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_abs_cuda(at::TensorList self); +TORCH_API void foreach_tensor_abs_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6d2b7cbc16108af2caae7873de47b64803a8bb47 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_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_abs { + 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_abs"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_abs(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_abs_ { + 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_abs_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_abs_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_abs_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_abs"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_abs.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos.h new file mode 100644 index 0000000000000000000000000000000000000000..e71ed221ff55aa6e5f93f6f77a558c41d07cb9f5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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::_foreach_acos(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_acos(at::TensorList self) { + return at::_ops::_foreach_acos::call(self); +} + +// aten::_foreach_acos_(Tensor(a!)[] self) -> () +inline void _foreach_acos_(at::TensorList self) { + return at::_ops::_foreach_acos_::call(self); +} + +// aten::_foreach_acos.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_acos_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_acos_out::call(self, out); +} +// aten::_foreach_acos.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_acos_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..954a2f86c02a5746c2993ef0bd0e396c8d318a63 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9e6ead7afc2d66735163b101bd2d0cb9edae0fc6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_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_acos(at::TensorList self); +TORCH_API void _foreach_acos_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_native.h new file mode 100644 index 0000000000000000000000000000000000000000..72c2ab0774cd5917c09c3ff415812a969d15cfce --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_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_acos_slow(at::TensorList self); +TORCH_API void _foreach_acos_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_acos_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_acos_cuda(at::TensorList self); +TORCH_API void foreach_tensor_acos_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5c2113c2498532be1181b457365d02136033156d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_acos_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_acos { + 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_acos"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_acos(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_acos_ { + 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_acos_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_acos_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_acos_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_acos"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_acos.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add.h new file mode 100644 index 0000000000000000000000000000000000000000..65504d2b58603369658746651102a5b20481ce0d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add.h @@ -0,0 +1,107 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_add.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_add_Scalar::call(self, scalar); +} + +// aten::_foreach_add_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_add_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_add__Scalar::call(self, scalar); +} + +// aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_List::call(self, other, alpha); +} + +// aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () +inline void _foreach_add_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add__List::call(self, other, alpha); +} + +// aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_add_ScalarList::call(self, scalars); +} + +// aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_add_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_add__ScalarList::call(self, scalars); +} + +// aten::_foreach_add.Tensor(Tensor[] self, Tensor other, *, Scalar alpha=1) -> Tensor[] +inline ::std::vector _foreach_add(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_Tensor::call(self, other, alpha); +} + +// aten::_foreach_add_.Tensor(Tensor(a!)[] self, Tensor other, *, Scalar alpha=1) -> () +inline void _foreach_add_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add__Tensor::call(self, other, alpha); +} + +// aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_add_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_add_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_List_out::call(self, other, alpha, out); +} +// aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out) { + return at::_ops::_foreach_add_List_out::call(self, other, alpha, out); +} + +// aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_add_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_add_ScalarList_out::call(self, scalars, out); +} + +// aten::_foreach_add.Tensor_out(Tensor[] self, Tensor other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_out(at::TensorList out, at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_add_Tensor_out::call(self, other, alpha, out); +} +// aten::_foreach_add.Tensor_out(Tensor[] self, Tensor other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_add_outf(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, at::TensorList out) { + return at::_ops::_foreach_add_Tensor_out::call(self, other, alpha, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..63a56f00f2f0477d7674a989b8180a41b72933f2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c10d0ee812d27a0ba70137e4e7926627b5e7649 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_add(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_add_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_add(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector _foreach_add(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_add_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_add(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c7b0981bf97ae20e08ed545b964596e381249342 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_native.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_add_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_add_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_add_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_add_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_add_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_add_list_kernel_slow(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_List_out(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +TORCH_API void foreach_tensor_add_list_kernel_slow_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_add_list_kernel_cuda(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_add_list_kernel_cuda_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_add_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_add_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_add_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_add_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_add_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_add_tensor_kernel_slow(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_Tensor_out(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, at::TensorList out); +TORCH_API void foreach_tensor_add_tensor_kernel_slow_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_add_tensor_kernel_cuda(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_add_tensor_kernel_cuda_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..56952175b8e9f5cac9206ee7ab25e919f6680f07 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_ops.h @@ -0,0 +1,155 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_add_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_add"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_add.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_add__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_add_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_add_.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_add_List { + using schema = ::std::vector (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_add"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_add__List { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_add_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> ()"; + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_add_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_add"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_add.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_add__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_add_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_add_.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_add_Tensor { + using schema = ::std::vector (at::TensorList, 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::_foreach_add"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_add.Tensor(Tensor[] self, Tensor other, *, Scalar alpha=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_add__Tensor { + using schema = void (at::TensorList, 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::_foreach_add_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_add_.Tensor(Tensor(a!)[] self, Tensor other, *, Scalar alpha=1) -> ()"; + static void call(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_add_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_add"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_add.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_add_List_out { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_add"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +}; + +struct TORCH_API _foreach_add_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_add"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_add_Tensor_out { + using schema = void (at::TensorList, const at::Tensor &, 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_add"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_add.Tensor_out(Tensor[] self, Tensor other, *, Scalar alpha=1, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv.h new file mode 100644 index 0000000000000000000000000000000000000000..3c7ab8a8d23c1c6153a7ed336f1f305753a9a121 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv.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_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] +inline ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1) { + return at::_ops::_foreach_addcdiv_Scalar::call(self, tensor1, tensor2, value); +} + +// aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars) { + return at::_ops::_foreach_addcdiv_ScalarList::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] +inline ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { + return at::_ops::_foreach_addcdiv_Tensor::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () +inline void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1) { + return at::_ops::_foreach_addcdiv__Scalar::call(self, tensor1, tensor2, value); +} + +// aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () +inline void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars) { + return at::_ops::_foreach_addcdiv__ScalarList::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () +inline void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { + return at::_ops::_foreach_addcdiv__Tensor::call(self, tensor1, tensor2, scalars); +} + +// aten::_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () +inline void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1) { + return at::_ops::_foreach_addcdiv_Scalar_out::call(self, tensor1, tensor2, value, out); +} +// aten::_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () +inline void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out) { + return at::_ops::_foreach_addcdiv_Scalar_out::call(self, tensor1, tensor2, value, out); +} + +// aten::_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars) { + return at::_ops::_foreach_addcdiv_ScalarList_out::call(self, tensor1, tensor2, scalars, out); +} +// aten::_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_addcdiv_ScalarList_out::call(self, tensor1, tensor2, scalars, out); +} + +// aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { + return at::_ops::_foreach_addcdiv_Tensor_out::call(self, tensor1, tensor2, scalars, out); +} +// aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out) { + return at::_ops::_foreach_addcdiv_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3180f268873f9d3b76f1be8e3d4362df0a2f778 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_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_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e0fb5ed26bf069175d7259041894d07fb44c5266 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_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::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..59a7272fd680bf0dd1dc99e8d81246c56f123b5a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_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_addcdiv_scalar_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_Scalar_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void foreach_tensor_addcdiv_scalar_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalar_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void foreach_tensor_addcdiv_scalar_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalarlist_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_ScalarList_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_addcdiv_scalarlist_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalarlist_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void foreach_tensor_addcdiv_scalarlist_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_addcdiv_tensor_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_Tensor_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void foreach_tensor_addcdiv_tensor_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API ::std::vector foreach_tensor_addcdiv_tensor_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void foreach_tensor_addcdiv_tensor_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b58c8e0ee20b3fe10b90aff8fdfaa5fcbc4ec25c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_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_addcdiv_Scalar { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); +}; + +struct TORCH_API _foreach_addcdiv_ScalarList { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_addcdiv_Tensor { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +}; + +struct TORCH_API _foreach_addcdiv__Scalar { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); +}; + +struct TORCH_API _foreach_addcdiv__ScalarList { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_addcdiv__Tensor { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +}; + +struct TORCH_API _foreach_addcdiv_Scalar_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +}; + +struct TORCH_API _foreach_addcdiv_ScalarList_out { + using schema = void (at::TensorList, at::TensorList, 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_addcdiv"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_addcdiv_Tensor_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul.h new file mode 100644 index 0000000000000000000000000000000000000000..132f3c8b1ea46a5e390f1f24d73d1d7322b04ad0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ea6b500a510ca8528f510fcefa47c4f77cd66387 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_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_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c055991d748f53163e87aa1abba71df21f01d7b5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_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::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..28971f0626c3da2d935416ba0a04723e0391f1c3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_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_addcmul_scalar_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_Scalar_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void foreach_tensor_addcmul_scalar_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector foreach_tensor_addcmul_scalar_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void foreach_tensor_addcmul_scalar_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector foreach_tensor_addcmul_scalarlist_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_ScalarList_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_addcmul_scalarlist_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_addcmul_scalarlist_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void foreach_tensor_addcmul_scalarlist_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_addcmul_tensor_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_Tensor_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void foreach_tensor_addcmul_tensor_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API ::std::vector foreach_tensor_addcmul_tensor_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void foreach_tensor_addcmul_tensor_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..781225c2b2a05de5fc0a7f59d077cbc6ea3ec8c4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_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_addcmul_Scalar { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); +}; + +struct TORCH_API _foreach_addcmul_ScalarList { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_addcmul_Tensor { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_addcmul.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +}; + +struct TORCH_API _foreach_addcmul__Scalar { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); +}; + +struct TORCH_API _foreach_addcmul__ScalarList { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_addcmul__Tensor { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_addcmul_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +}; + +struct TORCH_API _foreach_addcmul_Scalar_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_addcmul.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +}; + +struct TORCH_API _foreach_addcmul_ScalarList_out { + using schema = void (at::TensorList, at::TensorList, 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_addcmul"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_addcmul.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_addcmul_Tensor_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcmul"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin.h new file mode 100644 index 0000000000000000000000000000000000000000..0d2f4593a28ce22251a9bec54095b180ec346467 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin.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_asin(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_asin(at::TensorList self) { + return at::_ops::_foreach_asin::call(self); +} + +// aten::_foreach_asin_(Tensor(a!)[] self) -> () +inline void _foreach_asin_(at::TensorList self) { + return at::_ops::_foreach_asin_::call(self); +} + +// aten::_foreach_asin.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_asin_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_asin_out::call(self, out); +} +// aten::_foreach_asin.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_asin_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_asin_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d4a3f5d8c82e738698a4c4ee7e9c0fd8108cde9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_asin(at::TensorList self); +TORCH_API void _foreach_asin_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_asin_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_asin_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..028c366fa550ac4110af5a6bec5445273458d1f9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_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_asin(at::TensorList self); +TORCH_API void _foreach_asin_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bfca355ddd7c7ac8f9dcfa3995e4a72e9254cd42 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_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_asin_slow(at::TensorList self); +TORCH_API void _foreach_asin_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_asin_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_asin_cuda(at::TensorList self); +TORCH_API void foreach_tensor_asin_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0bf722dbaa99f78ca5cae705cbf210d2f0fcdf2f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_asin { + 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_asin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_asin(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_asin_ { + 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_asin_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_asin_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_asin_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_asin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_asin.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan.h new file mode 100644 index 0000000000000000000000000000000000000000..1b26ba7932c7e2d44f7469cd740668c290e38448 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan.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_atan(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_atan(at::TensorList self) { + return at::_ops::_foreach_atan::call(self); +} + +// aten::_foreach_atan_(Tensor(a!)[] self) -> () +inline void _foreach_atan_(at::TensorList self) { + return at::_ops::_foreach_atan_::call(self); +} + +// aten::_foreach_atan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_atan_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_atan_out::call(self, out); +} +// aten::_foreach_atan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_atan_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_atan_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7376cf29c88bf5f075b938c284e581e4855f778 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_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_atan(at::TensorList self); +TORCH_API void _foreach_atan_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_atan_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_atan_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..806fb46ef53acf277f206188cce7f089b20d9133 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_atan(at::TensorList self); +TORCH_API void _foreach_atan_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6e47b3ea385055158464b3cf2e8b0daa50a1f0ec --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_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_atan_slow(at::TensorList self); +TORCH_API void _foreach_atan_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_atan_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_atan_cuda(at::TensorList self); +TORCH_API void foreach_tensor_atan_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8b6f92b7d31f371e2c67738f7e133b088648aa88 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil.h new file mode 100644 index 0000000000000000000000000000000000000000..7de2f13b840c4023e2a979ca6f0aad5dd9168c5b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil.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_ceil(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_ceil(at::TensorList self) { + return at::_ops::_foreach_ceil::call(self); +} + +// aten::_foreach_ceil_(Tensor(a!)[] self) -> () +inline void _foreach_ceil_(at::TensorList self) { + return at::_ops::_foreach_ceil_::call(self); +} + +// aten::_foreach_ceil.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_ceil_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_ceil_out::call(self, out); +} +// aten::_foreach_ceil.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_ceil_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_ceil_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f2085be4faa472a4852a3ed33c6104ccc32c75c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_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_ceil(at::TensorList self); +TORCH_API void _foreach_ceil_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_ceil_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_ceil_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..03f2408d75d2b815a4fbb122132dfb9b80786048 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_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_ceil(at::TensorList self); +TORCH_API void _foreach_ceil_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_native.h new file mode 100644 index 0000000000000000000000000000000000000000..835d543f0b326f4b6e43bbeb8268d400da1b2b17 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_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_ceil_slow(at::TensorList self); +TORCH_API void _foreach_ceil_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_ceil_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_ceil_cuda(at::TensorList self); +TORCH_API void foreach_tensor_ceil_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8eb672096e648a0f9fe9cbaaf2bf96491f1cd23a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max.h new file mode 100644 index 0000000000000000000000000000000000000000..56d90ca7e84b9fbf4ab5f6348c93d14c856c69e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max.h @@ -0,0 +1,88 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_clamp_max(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_max_Scalar::call(self, scalar); +} + +// aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_clamp_max_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_max__Scalar::call(self, scalar); +} + +// aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_clamp_max(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_max_List::call(self, other); +} + +// aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_clamp_max_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_max__List::call(self, other); +} + +// aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_clamp_max(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_max_ScalarList::call(self, scalars); +} + +// aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_clamp_max_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_max__ScalarList::call(self, scalars); +} + +// aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_clamp_max_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_clamp_max_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_clamp_max_List_out::call(self, other, out); +} +// aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_clamp_max_List_out::call(self, other, out); +} + +// aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_clamp_max_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_clamp_max_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_clamp_max_ScalarList_out::call(self, scalars, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..76eada4e133de7274b8073b6a848909b26518b97 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_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_clamp_max(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_max_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_clamp_max_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_clamp_max(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_max_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_clamp_max_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_clamp_max(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_max_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_max_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_clamp_max_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f2f397c780b26b4ac9ec09ae32bc993c67d29967 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_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::vector _foreach_clamp_max(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_max_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_clamp_max(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_max_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_clamp_max(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_max_(at::TensorList self, at::ArrayRef scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1b20a06a15d4b549daa6c942819ebfb8d404e666 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_native.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_clamp_max_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_max_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_clamp_max_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_max_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_max_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_max_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_clamp_max_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_max_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_clamp_max_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9ea65dc7f4beb94ec97a89a7ed8c24b82402decc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_max_ops.h @@ -0,0 +1,122 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_clamp_max_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_max__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_max_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_max__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_max_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_max__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_max_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_max_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_max_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_max"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_clamp_max.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min.h new file mode 100644 index 0000000000000000000000000000000000000000..71735f403d00feee4e7d176a9ec03be7b8474d1e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ef92de11566ba3ad87f590dc9a442066f2c56b86 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_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_clamp_min(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_min_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_clamp_min_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_clamp_min(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_min_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_clamp_min_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_clamp_min(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_min_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_clamp_min_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ceec46773fc6793695cc65168ec06732324a531 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_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::vector _foreach_clamp_min(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_min_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_clamp_min(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_min_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_clamp_min(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_min_(at::TensorList self, at::ArrayRef scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0b793c28aa47248db77eea0d3525541824021d54 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_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_clamp_min_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_clamp_min_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_clamp_min_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5f68ca4e784f718aebe0807010b2a1358bf757e5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_ops.h @@ -0,0 +1,122 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_clamp_min_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_min__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_min_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_min__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_min_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_min__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_min_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_min_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_min_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_clamp_min"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..eca5d87e4c757f946fc446cf4bb6df313f30b5c1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..86941468c68f68d932887f58bf6ff3ed9305e328 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_copy(at::TensorList self, at::TensorList src, bool non_blocking=false); +TORCH_API void _foreach_copy_out(at::TensorList out, at::TensorList self, at::TensorList src, bool non_blocking=false); +TORCH_API void _foreach_copy_outf(at::TensorList self, at::TensorList src, bool non_blocking, at::TensorList out); +TORCH_API void _foreach_copy_(at::TensorList self, at::TensorList src, bool non_blocking=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3ab773fd9d3a3afa432ddc328b7a050ab5b856a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _foreach_copy_(at::TensorList self, at::TensorList src, bool non_blocking=false); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c4487866baad403fd476b810a82b418e4c033f5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector _foreach_copy(at::TensorList self, at::TensorList src, bool non_blocking=false); +TORCH_API void _foreach_copy_out(at::TensorList self, at::TensorList src, bool non_blocking, at::TensorList out); +TORCH_API void foreach_tensor_copy_list_kernel_slow_(at::TensorList self, at::TensorList src, bool non_blocking=false); +TORCH_API void foreach_tensor_copy_list_kernel_cuda_(at::TensorList self, at::TensorList src, bool non_blocking=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3b4c01740229c0ec6d91db096775bae07656116b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_copy_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_copy_ { + using schema = void (at::TensorList, at::TensorList, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_copy_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_copy_(Tensor(a!)[] self, Tensor[] src, bool non_blocking=False) -> ()"; + static void call(at::TensorList self, at::TensorList src, bool non_blocking); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList src, bool non_blocking); +}; + +struct TORCH_API _foreach_copy { + using schema = ::std::vector (at::TensorList, at::TensorList, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_copy(Tensor[] self, Tensor[] src, bool non_blocking=False) -> Tensor[] self_out"; + static ::std::vector call(at::TensorList self, at::TensorList src, bool non_blocking); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList src, bool non_blocking); +}; + +struct TORCH_API _foreach_copy_out { + using schema = void (at::TensorList, at::TensorList, bool, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_copy.out(Tensor[] self, Tensor[] src, bool non_blocking=False, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList src, bool non_blocking, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList src, bool non_blocking, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos.h new file mode 100644 index 0000000000000000000000000000000000000000..2aff126d2993baf12d8d5b32c66b18fb92b5de0e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos.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_cos(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_cos(at::TensorList self) { + return at::_ops::_foreach_cos::call(self); +} + +// aten::_foreach_cos_(Tensor(a!)[] self) -> () +inline void _foreach_cos_(at::TensorList self) { + return at::_ops::_foreach_cos_::call(self); +} + +// aten::_foreach_cos.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_cos_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_cos_out::call(self, out); +} +// aten::_foreach_cos.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_cos_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_cos_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44782687ccd7c4467977cab344c06dbadb2eafee --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_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_cos(at::TensorList self); +TORCH_API void _foreach_cos_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_cos_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_cos_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..05f3b102bb43fa26ab2bee8cb8331446faac491e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_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_cos(at::TensorList self); +TORCH_API void _foreach_cos_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d086912353c24932707d866ac0fac91f0d66e74c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_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_cos_slow(at::TensorList self); +TORCH_API void _foreach_cos_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_cos_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_cos_cuda(at::TensorList self); +TORCH_API void foreach_tensor_cos_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fc1e1653a2861bc414b3ff625e5dc5c03891b153 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cos_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_cos { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cos"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cos(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cos_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cos_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cos_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cos_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cos"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_cos.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh.h new file mode 100644 index 0000000000000000000000000000000000000000..530e50b77981d02473596721e102d22842118799 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh.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_cosh(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_cosh(at::TensorList self) { + return at::_ops::_foreach_cosh::call(self); +} + +// aten::_foreach_cosh_(Tensor(a!)[] self) -> () +inline void _foreach_cosh_(at::TensorList self) { + return at::_ops::_foreach_cosh_::call(self); +} + +// aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_cosh_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_cosh_out::call(self, out); +} +// aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_cosh_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_cosh_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d1f62c494da42c617fad4248d37e9d3d20deaa9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_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_cosh(at::TensorList self); +TORCH_API void _foreach_cosh_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_cosh_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_cosh_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91f07cf6822a693273b6fcdbb30551263121ac5e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_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_cosh(at::TensorList self); +TORCH_API void _foreach_cosh_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ee98911a1e757b549d52305bb3f6afe04e484200 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e3bd31e232b6c6102f5b17931b93808b1369c5bf --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_cosh { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cosh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cosh(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cosh_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cosh_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_cosh_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_cosh_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_cosh"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div.h new file mode 100644 index 0000000000000000000000000000000000000000..dd52108fadfd18843dfa21dd274c6c694e2a70f7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div.h @@ -0,0 +1,107 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_div.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_div_Scalar::call(self, scalar); +} + +// aten::_foreach_div_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_div_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_div__Scalar::call(self, scalar); +} + +// aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_div_List::call(self, other); +} + +// aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_div_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_div__List::call(self, other); +} + +// aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_div_ScalarList::call(self, scalars); +} + +// aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_div_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_div__ScalarList::call(self, scalars); +} + +// aten::_foreach_div.Tensor(Tensor[] self, Tensor other) -> Tensor[] +inline ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_div_Tensor::call(self, other); +} + +// aten::_foreach_div_.Tensor(Tensor(a!)[] self, Tensor other) -> () +inline void _foreach_div_(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_div__Tensor::call(self, other); +} + +// aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_div_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_div_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_div_List_out::call(self, other, out); +} +// aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_div_List_out::call(self, other, out); +} + +// aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_div_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_div_ScalarList_out::call(self, scalars, out); +} + +// aten::_foreach_div.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_div_Tensor_out::call(self, other, out); +} +// aten::_foreach_div.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_div_outf(at::TensorList self, const at::Tensor & other, at::TensorList out) { + return at::_ops::_foreach_div_Tensor_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bf7012f7f665403d03721a1875f9f8da2add267 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_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_div(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_outf(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, const at::Tensor & other); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a3fc6e5b5c80c957def1b0ce334fa4bf1d57cd3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 ::std::vector _foreach_div(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_(at::TensorList 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_native.h new file mode 100644 index 0000000000000000000000000000000000000000..da38d2765fd2e259f584ffa2ff6482b1734cf135 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_native.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_div_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_div_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_div_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_div_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_div_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_div_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_div_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_div_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_div_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_div_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_div_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_div_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_div_tensor_kernel_slow(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_Tensor_out(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void foreach_tensor_div_tensor_kernel_slow_(at::TensorList self, const at::Tensor & other); +TORCH_API ::std::vector foreach_tensor_div_tensor_kernel_cuda(at::TensorList self, const at::Tensor & other); +TORCH_API void foreach_tensor_div_tensor_kernel_cuda_(at::TensorList self, const at::Tensor & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..376daa0475e7949da9e6b052c28b25b63dbdf6af --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_ops.h @@ -0,0 +1,155 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_div_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_div"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_div.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_div__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_div_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_div_.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_div_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_div"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_div.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_div__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_div_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_div_.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_div_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_div"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_div.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_div__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_div_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_div_.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_div_Tensor { + using schema = ::std::vector (at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_div"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_div.Tensor(Tensor[] self, Tensor other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Tensor & other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other); +}; + +struct TORCH_API _foreach_div__Tensor { + using schema = void (at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_div_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_div_.Tensor(Tensor(a!)[] self, Tensor other) -> ()"; + static void call(at::TensorList self, const at::Tensor & other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other); +}; + +struct TORCH_API _foreach_div_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_div"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_div.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_div_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_div"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_div.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_div_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_div"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_div_Tensor_out { + using schema = void (at::TensorList, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_div"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_div.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Tensor & other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf.h new file mode 100644 index 0000000000000000000000000000000000000000..ea8ec05c4e2fe592c98deac3f5aa08189da2c5e4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf.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_erf(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_erf(at::TensorList self) { + return at::_ops::_foreach_erf::call(self); +} + +// aten::_foreach_erf_(Tensor(a!)[] self) -> () +inline void _foreach_erf_(at::TensorList self) { + return at::_ops::_foreach_erf_::call(self); +} + +// aten::_foreach_erf.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erf_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_erf_out::call(self, out); +} +// aten::_foreach_erf.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erf_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_erf_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..185bc138b31856ab2b1078b063c745da0f74eb80 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd89434196c846a36b02353e0a685a93bfd3fe8c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_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_erf(at::TensorList self); +TORCH_API void _foreach_erf_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..892d6eea91628c3c98043082833b7ee4b36c710c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8e9ff74e133db2b4853a2130cfb42dc9a1d43e4a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_erf { + 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_erf"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_erf(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_erf_ { + 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_erf_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_erf_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_erf_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_erf"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_erf.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc.h new file mode 100644 index 0000000000000000000000000000000000000000..e08c1416b3ac471d499745939e79a4956aeee78f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_erfc(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_erfc(at::TensorList self) { + return at::_ops::_foreach_erfc::call(self); +} + +// aten::_foreach_erfc_(Tensor(a!)[] self) -> () +inline void _foreach_erfc_(at::TensorList self) { + return at::_ops::_foreach_erfc_::call(self); +} + +// aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erfc_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_erfc_out::call(self, out); +} +// aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erfc_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_erfc_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1675b0c0352a7876c9c8b998365edfa9944917b2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_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_erfc(at::TensorList self); +TORCH_API void _foreach_erfc_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_erfc_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_erfc_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a095dfe6f8dbf93c1390b37474c53ea261263ee9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_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_erfc(at::TensorList self); +TORCH_API void _foreach_erfc_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ce518f67a970580cc01d5f8d0f09b89ed4ac3392 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_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_erfc_slow(at::TensorList self); +TORCH_API void _foreach_erfc_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_erfc_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_erfc_cuda(at::TensorList self); +TORCH_API void foreach_tensor_erfc_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2da4ff5b3194282aba2e8dad36f39cd93c298fe9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_erfc { + 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_erfc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_erfc(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_erfc_ { + 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_erfc_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_erfc_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_erfc_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_erfc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_erfc.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp.h new file mode 100644 index 0000000000000000000000000000000000000000..62a0cdcb5eaaf47958431ac321fc8f3603785769 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp.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_exp(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_exp(at::TensorList self) { + return at::_ops::_foreach_exp::call(self); +} + +// aten::_foreach_exp_(Tensor(a!)[] self) -> () +inline void _foreach_exp_(at::TensorList self) { + return at::_ops::_foreach_exp_::call(self); +} + +// aten::_foreach_exp.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_exp_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_exp_out::call(self, out); +} +// aten::_foreach_exp.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_exp_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_exp_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b0f77a02fb6dc420fcf08339c70d3b047cde0cad --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_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_exp(at::TensorList self); +TORCH_API void _foreach_exp_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_exp_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_exp_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7b544c65d6ef68f6ea99c785c774b75e6ad29be4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_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_exp(at::TensorList self); +TORCH_API void _foreach_exp_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c7b0048cc3617d9228ab311ff20510f980511107 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_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_exp_slow(at::TensorList self); +TORCH_API void _foreach_exp_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_exp_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_exp_cuda(at::TensorList self); +TORCH_API void foreach_tensor_exp_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_exp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..22d032c7d5fb8327bf4007ab5b7009d69a5c97e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1.h new file mode 100644 index 0000000000000000000000000000000000000000..e7e09f65e5decfdaf0d0f974f4055798d1b1185e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..449a5f3d324481e3eed65d4e66888977a4fe98f0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_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_expm1(at::TensorList self); +TORCH_API void _foreach_expm1_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_expm1_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_expm1_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..98c3a2e937b8a2ffe1885133a4d421e9c8ded3cc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_expm1(at::TensorList self); +TORCH_API void _foreach_expm1_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3ae99eca64892403a1be02b0d75a4f0d94964863 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_expm1_slow(at::TensorList self); +TORCH_API void _foreach_expm1_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_expm1_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_expm1_cuda(at::TensorList self); +TORCH_API void foreach_tensor_expm1_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..113b6c4664675f204057f75f7bc6f2abb3fdef1f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_expm1_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_expm1 { + 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_expm1"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_expm1(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_expm1_ { + 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_expm1_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_expm1_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_expm1_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_expm1"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_expm1.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor.h new file mode 100644 index 0000000000000000000000000000000000000000..4c728d650899725365244926f0c29f209b6d096a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eebf66a88b9303f4a283f2bdcb53087d63750d01 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_floor(at::TensorList self); +TORCH_API void _foreach_floor_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_floor_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_floor_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0be7ba11f7a784331e7c586ec036b8b3c72210b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_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_floor(at::TensorList self); +TORCH_API void _foreach_floor_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..737c0c6c52189ff1cfd78e4f164db4a8dcdd08c2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_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_floor_slow(at::TensorList self); +TORCH_API void _foreach_floor_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_floor_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_floor_cuda(at::TensorList self); +TORCH_API void foreach_tensor_floor_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1388f6ff132be81c02478b3684496ba7c3ce210b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_floor_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_floor { + 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_floor"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_floor(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_floor_ { + 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_floor_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_floor_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_floor_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_floor"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_floor.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac.h new file mode 100644 index 0000000000000000000000000000000000000000..2742e5cd2f6300b6770bf1905dc9c0f2a5f29cd4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac.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_frac(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_frac(at::TensorList self) { + return at::_ops::_foreach_frac::call(self); +} + +// aten::_foreach_frac_(Tensor(a!)[] self) -> () +inline void _foreach_frac_(at::TensorList self) { + return at::_ops::_foreach_frac_::call(self); +} + +// aten::_foreach_frac.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_frac_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_frac_out::call(self, out); +} +// aten::_foreach_frac.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_frac_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_frac_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2573672e8a7a82a9341eaebd6be99358b63f890e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_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_frac(at::TensorList self); +TORCH_API void _foreach_frac_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_frac_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_frac_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb4c773498213cd132e3a21e637e33a2c793d133 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_frac(at::TensorList self); +TORCH_API void _foreach_frac_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c6d3beac4b52617a48ddd33cb77303ead4bb48ad --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_frac_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..45e70fd5377ab3dcf9f31491c5a83a346177870c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_frac { + 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_frac"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_frac(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_frac_ { + 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_frac_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_frac_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_frac_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_frac"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_frac.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp.h new file mode 100644 index 0000000000000000000000000000000000000000..3e3b604a83a59301a08bc967552ab9c799c46285 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp.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_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] +inline ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::TensorList weights) { + return at::_ops::_foreach_lerp_List::call(self, tensors1, weights); +} + +// aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () +inline void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::TensorList weights) { + return at::_ops::_foreach_lerp__List::call(self, tensors1, weights); +} + +// aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] +inline ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { + return at::_ops::_foreach_lerp_Scalar::call(self, tensors1, weight); +} + +// aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () +inline void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { + return at::_ops::_foreach_lerp__Scalar::call(self, tensors1, weight); +} + +// aten::_foreach_lerp.ScalarList(Tensor[] self, Tensor[] tensors1, Scalar[] weight) -> Tensor[] +inline ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight) { + return at::_ops::_foreach_lerp_ScalarList::call(self, tensors1, weight); +} + +// aten::_foreach_lerp_.ScalarList(Tensor(a!)[] self, Tensor[] tensors1, Scalar[] weight) -> () +inline void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight) { + return at::_ops::_foreach_lerp__ScalarList::call(self, tensors1, weight); +} + +// aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () +inline void _foreach_lerp_out(at::TensorList out, at::TensorList self, at::TensorList tensors1, at::TensorList weights) { + return at::_ops::_foreach_lerp_List_out::call(self, tensors1, weights, out); +} +// aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () +inline void _foreach_lerp_outf(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out) { + return at::_ops::_foreach_lerp_List_out::call(self, tensors1, weights, out); +} + +// aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () +inline void _foreach_lerp_out(at::TensorList out, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { + return at::_ops::_foreach_lerp_Scalar_out::call(self, tensors1, weight, out); +} +// aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () +inline void _foreach_lerp_outf(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out) { + return at::_ops::_foreach_lerp_Scalar_out::call(self, tensors1, weight, out); +} + +// aten::_foreach_lerp.ScalarList_out(Tensor[] self, Tensor[] tensors1, Scalar[] weight, *, Tensor(a!)[] out) -> () +inline void _foreach_lerp_out(at::TensorList out, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight) { + return at::_ops::_foreach_lerp_ScalarList_out::call(self, tensors1, weight, out); +} +// aten::_foreach_lerp.ScalarList_out(Tensor[] self, Tensor[] tensors1, Scalar[] weight, *, Tensor(a!)[] out) -> () +inline void _foreach_lerp_outf(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, at::TensorList out) { + return at::_ops::_foreach_lerp_ScalarList_out::call(self, tensors1, weight, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e254d0b0c51d0b8a2791061e41c016fc1dc69dd --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_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_lerp(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API void _foreach_lerp_out(at::TensorList out, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API void _foreach_lerp_outf(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API void _foreach_lerp_out(at::TensorList out, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API void _foreach_lerp_outf(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API void _foreach_lerp_out(at::TensorList out, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API void _foreach_lerp_outf(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, at::TensorList out); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4d294fb2301f1444aba01d68051f3d333f542242 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_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::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::ArrayRef 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c4c652d7de84f87e966eeaff9c053da31b1b95c2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_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_ternary_lerp_slow(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API void _foreach_lerp_List_out(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); +TORCH_API void foreach_tensor_ternary_lerp_slow_(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API ::std::vector foreach_tensor_lerp_ternary_cuda(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API void foreach_tensor_lerp_ternary_cuda_(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API ::std::vector foreach_tensor_lerp_list_kernel_slow(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API void _foreach_lerp_Scalar_out(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); +TORCH_API void foreach_tensor_lerp_list_kernel_slow_(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API ::std::vector foreach_tensor_lerp_list_cuda(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API void foreach_tensor_lerp_list_cuda_(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API ::std::vector foreach_tensor_lerp_scalarlist_kernel_slow(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API void _foreach_lerp_ScalarList_out(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, at::TensorList out); +TORCH_API void foreach_tensor_lerp_scalarlist_kernel_slow_(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API ::std::vector foreach_tensor_lerp_scalarlist_cuda(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API void foreach_tensor_lerp_scalarlist_cuda_(at::TensorList self, at::TensorList tensors1, at::ArrayRef 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6b5ef0aec636dc312ab444db84db4ba28737abf8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_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_lerp_List { + using schema = ::std::vector (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_lerp"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensors1, at::TensorList weights); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +}; + +struct TORCH_API _foreach_lerp__List { + 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_lerp_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::TensorList weights); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +}; + +struct TORCH_API _foreach_lerp_Scalar { + using schema = ::std::vector (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +}; + +struct TORCH_API _foreach_lerp__Scalar { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +}; + +struct TORCH_API _foreach_lerp_ScalarList { + using schema = ::std::vector (at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_lerp.ScalarList(Tensor[] self, Tensor[] tensors1, Scalar[] weight) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +}; + +struct TORCH_API _foreach_lerp__ScalarList { + using schema = void (at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_lerp_.ScalarList(Tensor(a!)[] self, Tensor[] tensors1, Scalar[] weight) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +}; + +struct TORCH_API _foreach_lerp_List_out { + using schema = void (at::TensorList, 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_lerp"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); +}; + +struct TORCH_API _foreach_lerp_Scalar_out { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); +}; + +struct TORCH_API _foreach_lerp_ScalarList_out { + using schema = void (at::TensorList, 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_lerp"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_lerp.ScalarList_out(Tensor[] self, Tensor[] tensors1, Scalar[] weight, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma.h new file mode 100644 index 0000000000000000000000000000000000000000..aa3b0b322d9d2ff97c7a14d95c0a0de2c660d0c6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma.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_lgamma(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_lgamma(at::TensorList self) { + return at::_ops::_foreach_lgamma::call(self); +} + +// aten::_foreach_lgamma_(Tensor(a!)[] self) -> () +inline void _foreach_lgamma_(at::TensorList self) { + return at::_ops::_foreach_lgamma_::call(self); +} + +// aten::_foreach_lgamma.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_lgamma_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_lgamma_out::call(self, out); +} +// aten::_foreach_lgamma.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_lgamma_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_lgamma_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f873be477b570b9536be8ebc4640c7dc22704062 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_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_lgamma(at::TensorList self); +TORCH_API void _foreach_lgamma_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_lgamma_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_lgamma_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f99825446343eb1b43daf3f8dc4e913dceb1da35 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_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_lgamma(at::TensorList self); +TORCH_API void _foreach_lgamma_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2294cf599f2c68cc36c811e0d67fd5603352a848 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_lgamma_slow(at::TensorList self); +TORCH_API void _foreach_lgamma_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_lgamma_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_lgamma_cuda(at::TensorList self); +TORCH_API void foreach_tensor_lgamma_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ff8d0e67a0cad09a3cf4d68858674c29e179a2de --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_lgamma { + 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_lgamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_lgamma(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_lgamma_ { + 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_lgamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_lgamma_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_lgamma_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_lgamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_lgamma.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log.h new file mode 100644 index 0000000000000000000000000000000000000000..97f5c5fb0da1dbd7dc3ad93a9809faee337b7d29 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log.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_log(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log(at::TensorList self) { + return at::_ops::_foreach_log::call(self); +} + +// aten::_foreach_log_(Tensor(a!)[] self) -> () +inline void _foreach_log_(at::TensorList self) { + return at::_ops::_foreach_log_::call(self); +} + +// aten::_foreach_log.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log_out::call(self, out); +} +// aten::_foreach_log.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10.h new file mode 100644 index 0000000000000000000000000000000000000000..c76fd9fdf9ec4d80c9a271986591810b9c6c1662 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10.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_log10(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log10(at::TensorList self) { + return at::_ops::_foreach_log10::call(self); +} + +// aten::_foreach_log10_(Tensor(a!)[] self) -> () +inline void _foreach_log10_(at::TensorList self) { + return at::_ops::_foreach_log10_::call(self); +} + +// aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log10_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log10_out::call(self, out); +} +// aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log10_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log10_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79b143400e09d388ac66d9db1bce96554ccbd987 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_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_log10(at::TensorList self); +TORCH_API void _foreach_log10_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_log10_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_log10_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d5373c77ad7ccce7a6ca59b7ed3a8c391a74e31 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_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_log10(at::TensorList self); +TORCH_API void _foreach_log10_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_native.h new file mode 100644 index 0000000000000000000000000000000000000000..69d02f084f286423ba20a7c8e894051f33732103 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_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_log10_slow(at::TensorList self); +TORCH_API void _foreach_log10_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_log10_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_log10_cuda(at::TensorList self); +TORCH_API void foreach_tensor_log10_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..467f1210115b746f14e24b154e601e0708bda7e3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log10_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_log10 { + 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_log10"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log10(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log10_ { + 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_log10_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log10_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log10_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_log10"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_log10.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p.h new file mode 100644 index 0000000000000000000000000000000000000000..be5d53a95d2500c35294e76db3d14d2b7696b16f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p.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_log1p(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log1p(at::TensorList self) { + return at::_ops::_foreach_log1p::call(self); +} + +// aten::_foreach_log1p_(Tensor(a!)[] self) -> () +inline void _foreach_log1p_(at::TensorList self) { + return at::_ops::_foreach_log1p_::call(self); +} + +// aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log1p_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log1p_out::call(self, out); +} +// aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log1p_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log1p_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79fc0745674bf030b0ca713709d0641e12f804e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_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_log1p(at::TensorList self); +TORCH_API void _foreach_log1p_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_log1p_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_log1p_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..191adb29ac3be3d7d5572b27e18ce5b3032ee557 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_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_log1p(at::TensorList self); +TORCH_API void _foreach_log1p_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d9e789da87cdf027fa8321f229dbeeece7d8364c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_log1p_slow(at::TensorList self); +TORCH_API void _foreach_log1p_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_log1p_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_log1p_cuda(at::TensorList self); +TORCH_API void foreach_tensor_log1p_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..51f878c1edcaedbc82947e9b6c5098bc464ed1e2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_log1p { + 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_log1p"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log1p(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log1p_ { + 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_log1p_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log1p_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log1p_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_log1p"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_log1p.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2.h new file mode 100644 index 0000000000000000000000000000000000000000..6d40d8d6b0ec450bfdcf84c6481a390e0c23e681 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_log2(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log2(at::TensorList self) { + return at::_ops::_foreach_log2::call(self); +} + +// aten::_foreach_log2_(Tensor(a!)[] self) -> () +inline void _foreach_log2_(at::TensorList self) { + return at::_ops::_foreach_log2_::call(self); +} + +// aten::_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log2_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log2_out::call(self, out); +} +// aten::_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log2_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log2_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6a9bff3f7487e5be557a420d5b8e4dda41568c2d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_log2(at::TensorList self); +TORCH_API void _foreach_log2_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_log2_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_log2_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1bfb3a1b5a9a1e6b2b1a338098a470701035e1e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3b497e012361664e6bd316f307ebfd5efd76c425 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_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_log2_slow(at::TensorList self); +TORCH_API void _foreach_log2_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_log2_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_log2_cuda(at::TensorList self); +TORCH_API void foreach_tensor_log2_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3975432c10b7607f83d3b7ad7395ca86b7451af6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_log2 { + 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_log2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log2(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log2_ { + 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_log2_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log2_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log2_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_log2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_log2.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..41c5f8aeeddba0d0926092f0d1ed4b0c40b95afc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_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_log(at::TensorList self); +TORCH_API void _foreach_log_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_log_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_log_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e407a37dfb1ce1d5900503b286b1626016399456 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_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_log(at::TensorList self); +TORCH_API void _foreach_log_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_native.h new file mode 100644 index 0000000000000000000000000000000000000000..52cc1e85c6b39b263d8e09c9e01a661729714916 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_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_log_slow(at::TensorList self); +TORCH_API void _foreach_log_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_log_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_log_cuda(at::TensorList self); +TORCH_API void foreach_tensor_log_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f05148dd04d8cb3798944f707984d0829d281ec6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_log { + 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_log"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log_ { + 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_log_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_log_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log_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_log"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_log.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max.h new file mode 100644 index 0000000000000000000000000000000000000000..0d01ab3297e1e2d836e56e255f572dd4f46a8216 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..20e1172ec9b111a894f279b6d8cfb77e2b82f1bc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_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::vector _foreach_max(at::TensorList self); +TORCH_API void _foreach_max_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_max_outf(at::TensorList self, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..572baf17b4a3c5cc8fa05a26b675b0944e539336 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_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::vector _foreach_max(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_native.h new file mode 100644 index 0000000000000000000000000000000000000000..edfb500434af465f6ee3fc050df801bae6b52f02 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_max_slow(at::TensorList self); +TORCH_API void _foreach_max_out(at::TensorList self, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_max_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6bc4fdc506544a5b466b459255811545db59ad60 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_max_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_max { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_max"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_max(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_max_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_max"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_max.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum.h new file mode 100644 index 0000000000000000000000000000000000000000..67edb9b2d3523fde26f8b817455d53b47d5e18cd --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum.h @@ -0,0 +1,88 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum_Scalar::call(self, scalar); +} + +// aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_maximum_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum__Scalar::call(self, scalar); +} + +// aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum_List::call(self, other); +} + +// aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_maximum_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum__List::call(self, other); +} + +// aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum_ScalarList::call(self, scalars); +} + +// aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_maximum_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum__ScalarList::call(self, scalars); +} + +// aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_maximum_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum_List_out::call(self, other, out); +} +// aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_maximum_List_out::call(self, other, out); +} + +// aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_maximum_ScalarList_out::call(self, scalars, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7c5d28c9df07cfdacc607620ce9afa840527d42 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_compositeexplicitautograd_dispatch.h @@ -0,0 +1,39 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_maximum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_maximum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_maximum_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_maximum_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_maximum_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_maximum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_maximum_(at::TensorList self, at::ArrayRef scalars); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b4fc809bbb456e59dddfe02dc82246687dc296d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_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::vector _foreach_maximum(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_maximum_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_maximum_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_maximum(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_maximum_(at::TensorList self, at::ArrayRef scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..684640fd16881011f0f96b75d95183dd27d9a549 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cafe1772bdea2468c44b9d0a95ee75c43b2482b9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum.h new file mode 100644 index 0000000000000000000000000000000000000000..26a0821a087d3f3c11c23f936e9e3391776acf71 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..40d0ff50a781983a5442ee428401a57dc04b4ae1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aaddf8d67bd96a202c425253bf6b5ea9d2aeb719 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_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::vector _foreach_minimum(at::TensorList self, const at::Scalar & scalar); +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_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_minimum(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_minimum_(at::TensorList self, at::ArrayRef scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..10a69cd90f0a44d241abc1e3451eb7954349cd7a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_native.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_clamp_max_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_minimum_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_clamp_max_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_max_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_minimum_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_max_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_clamp_max_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_minimum_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_clamp_max_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_clamp_max_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_clamp_max_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d20d729a2c6063812ba7e6ca49d62d610ae8eae3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_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_minimum_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_minimum"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_minimum.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_minimum__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_minimum_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_minimum_.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_minimum_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_minimum"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_minimum.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_minimum__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_minimum_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_minimum_.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_minimum_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_minimum"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_minimum.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_minimum__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_minimum_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_minimum_.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_minimum_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_minimum"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_minimum.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_minimum_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_minimum"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_minimum.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_minimum_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_minimum"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_minimum.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul.h new file mode 100644 index 0000000000000000000000000000000000000000..09b9a7b1f8432a612349a91830af61f66e455a56 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul.h @@ -0,0 +1,107 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_mul.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_mul_Scalar::call(self, scalar); +} + +// aten::_foreach_mul_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_mul_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_mul__Scalar::call(self, scalar); +} + +// aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_mul_List::call(self, other); +} + +// aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_mul_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_mul__List::call(self, other); +} + +// aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_mul_ScalarList::call(self, scalars); +} + +// aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_mul_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_mul__ScalarList::call(self, scalars); +} + +// aten::_foreach_mul.Tensor(Tensor[] self, Tensor other) -> Tensor[] +inline ::std::vector _foreach_mul(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_mul_Tensor::call(self, other); +} + +// aten::_foreach_mul_.Tensor(Tensor(a!)[] self, Tensor other) -> () +inline void _foreach_mul_(at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_mul__Tensor::call(self, other); +} + +// aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_mul_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_mul_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_mul_List_out::call(self, other, out); +} +// aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_mul_List_out::call(self, other, out); +} + +// aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_mul_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_mul_ScalarList_out::call(self, scalars, out); +} + +// aten::_foreach_mul.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_out(at::TensorList out, at::TensorList self, const at::Tensor & other) { + return at::_ops::_foreach_mul_Tensor_out::call(self, other, out); +} +// aten::_foreach_mul.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> () +inline void _foreach_mul_outf(at::TensorList self, const at::Tensor & other, at::TensorList out) { + return at::_ops::_foreach_mul_Tensor_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4717a43a1e188d1b284e3ca6a18b4ca019f80830 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_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_mul(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_mul_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_mul_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_mul_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_mul(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_mul_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_mul_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_mul_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_mul(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_mul_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_mul_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_mul_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_mul(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_mul_out(at::TensorList out, at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_mul_outf(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void _foreach_mul_(at::TensorList self, const at::Tensor & other); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0c19458a8ee69e8cdb116ce9d55bc22dea8704b7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_cuda_dispatch.h @@ -0,0 +1,35 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_mul(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_mul_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_mul(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_mul_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_mul(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_mul_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_mul(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_mul_(at::TensorList 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..993273b3502c3ce7c16e45b7fa8a1026e8597b0d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_native.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_mul_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_mul_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_mul_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_mul_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_mul_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_mul_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_mul_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_mul_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_mul_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_mul_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_mul_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_mul_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_mul_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_mul_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_mul_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_mul_tensor_kernel_slow(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_mul_Tensor_out(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void foreach_tensor_mul_tensor_kernel_slow_(at::TensorList self, const at::Tensor & other); +TORCH_API ::std::vector foreach_tensor_mul_tensor_kernel_cuda(at::TensorList self, const at::Tensor & other); +TORCH_API void foreach_tensor_mul_tensor_kernel_cuda_(at::TensorList self, const at::Tensor & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..08e4083bd9ca0c19feb936dc12ff9d479b4478a8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_mul_ops.h @@ -0,0 +1,155 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_mul_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_mul.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_mul__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_mul_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_mul_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_mul__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_mul_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_mul__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_mul_Tensor { + using schema = ::std::vector (at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_mul.Tensor(Tensor[] self, Tensor other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Tensor & other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other); +}; + +struct TORCH_API _foreach_mul__Tensor { + using schema = void (at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_mul_.Tensor(Tensor(a!)[] self, Tensor other) -> ()"; + static void call(at::TensorList self, const at::Tensor & other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other); +}; + +struct TORCH_API _foreach_mul_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_mul_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_mul_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_mul_Tensor_out { + using schema = void (at::TensorList, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_mul"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_mul.Tensor_out(Tensor[] self, Tensor other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Tensor & other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & other, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg.h new file mode 100644 index 0000000000000000000000000000000000000000..e400795cbf916adadec14ff521363525624db41a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg.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_neg(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_neg(at::TensorList self) { + return at::_ops::_foreach_neg::call(self); +} + +// aten::_foreach_neg_(Tensor(a!)[] self) -> () +inline void _foreach_neg_(at::TensorList self) { + return at::_ops::_foreach_neg_::call(self); +} + +// aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_neg_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_neg_out::call(self, out); +} +// aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_neg_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_neg_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..59395b836e7085882652ca4d1d5d5f2d4ab547da --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_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_neg(at::TensorList self); +TORCH_API void _foreach_neg_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_neg_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_neg_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c9f4d0b4a88fc9272c61816859d2bc377d4d001 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_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_neg(at::TensorList self); +TORCH_API void _foreach_neg_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..707bdf0760ef7719099995449f7b6fa0ec870600 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d37826985accd96074b2e3152269f815af408f94 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg_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_neg { + 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_neg"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_neg(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_neg_ { + 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_neg_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_neg_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_neg_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_neg"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_neg.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..fb8d4e00acd7fadc8f66e60ce2cb64bbe1d1b6c9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2, ScalarType? dtype=None) -> Tensor[] +inline ::std::vector _foreach_norm(at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt) { + return at::_ops::_foreach_norm_Scalar::call(self, ord, dtype); +} + +// aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, ScalarType? dtype=None, *, Tensor(a!)[] out) -> () +inline void _foreach_norm_out(at::TensorList out, at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt) { + return at::_ops::_foreach_norm_Scalar_out::call(self, ord, dtype, out); +} +// aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, ScalarType? dtype=None, *, Tensor(a!)[] out) -> () +inline void _foreach_norm_outf(at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out) { + return at::_ops::_foreach_norm_Scalar_out::call(self, ord, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..46560929af08278236ac7848b4e0e9fbe683c4e3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_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::vector _foreach_norm(at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt); +TORCH_API void _foreach_norm_out(at::TensorList out, at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt); +TORCH_API void _foreach_norm_outf(at::TensorList self, const at::Scalar & ord, ::std::optional dtype, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0d415c565c93374ee145a9b5636019a5e48dcb1e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_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::vector _foreach_norm(at::TensorList self, const at::Scalar & ord=2, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..50ef46869442a9e2cfacbf96dee2106d22c65b5d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_norm_slow(at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt); +TORCH_API void _foreach_norm_Scalar_out(at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_norm_cuda(at::TensorList self, const at::Scalar & ord=2, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6e7cfe2cf98775eafcfb89c5fa19851e8b4bdea4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_norm_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_norm"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_norm.Scalar(Tensor[] self, Scalar ord=2, ScalarType? dtype=None) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & ord, ::std::optional dtype); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord, ::std::optional dtype); +}; + +struct TORCH_API _foreach_norm_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, ::std::optional, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_norm"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, ScalarType? dtype=None, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow.h new file mode 100644 index 0000000000000000000000000000000000000000..31c603594a093e4667c9db3d10d2b8b67cb70ea2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow.h @@ -0,0 +1,93 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated 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_pow.List(Tensor[] self, Tensor[] exponent) -> Tensor[] +inline ::std::vector _foreach_pow(at::TensorList self, at::TensorList exponent) { + return at::_ops::_foreach_pow_List::call(self, exponent); +} + +// aten::_foreach_pow.Scalar(Tensor[] self, Scalar exponent) -> Tensor[] +inline ::std::vector _foreach_pow(at::TensorList self, const at::Scalar & exponent) { + return at::_ops::_foreach_pow_Scalar::call(self, exponent); +} + +// aten::_foreach_pow.ScalarList(Tensor[] self, Scalar[] exponent) -> Tensor[] +inline ::std::vector _foreach_pow(at::TensorList self, at::ArrayRef exponent) { + return at::_ops::_foreach_pow_ScalarList::call(self, exponent); +} + +// aten::_foreach_pow.ScalarAndTensor(Scalar self, Tensor[] exponent) -> Tensor[] +inline ::std::vector _foreach_pow(const at::Scalar & self, at::TensorList exponent) { + return at::_ops::_foreach_pow_ScalarAndTensor::call(self, exponent); +} + +// aten::_foreach_pow_.List(Tensor(a!)[] self, Tensor[] exponent) -> () +inline void _foreach_pow_(at::TensorList self, at::TensorList exponent) { + return at::_ops::_foreach_pow__List::call(self, exponent); +} + +// aten::_foreach_pow_.Scalar(Tensor(a!)[] self, Scalar exponent) -> () +inline void _foreach_pow_(at::TensorList self, const at::Scalar & exponent) { + return at::_ops::_foreach_pow__Scalar::call(self, exponent); +} + +// aten::_foreach_pow_.ScalarList(Tensor(a!)[] self, Scalar[] exponent) -> () +inline void _foreach_pow_(at::TensorList self, at::ArrayRef exponent) { + return at::_ops::_foreach_pow__ScalarList::call(self, exponent); +} + +// aten::_foreach_pow.List_out(Tensor[] self, Tensor[] exponent, *, Tensor(a!)[] out) -> () +inline void _foreach_pow_out(at::TensorList out, at::TensorList self, at::TensorList exponent) { + return at::_ops::_foreach_pow_List_out::call(self, exponent, out); +} +// aten::_foreach_pow.List_out(Tensor[] self, Tensor[] exponent, *, Tensor(a!)[] out) -> () +inline void _foreach_pow_outf(at::TensorList self, at::TensorList exponent, at::TensorList out) { + return at::_ops::_foreach_pow_List_out::call(self, exponent, out); +} + +// aten::_foreach_pow.Scalar_out(Tensor[] self, Scalar exponent, *, Tensor(a!)[] out) -> () +inline void _foreach_pow_out(at::TensorList out, at::TensorList self, const at::Scalar & exponent) { + return at::_ops::_foreach_pow_Scalar_out::call(self, exponent, out); +} +// aten::_foreach_pow.Scalar_out(Tensor[] self, Scalar exponent, *, Tensor(a!)[] out) -> () +inline void _foreach_pow_outf(at::TensorList self, const at::Scalar & exponent, at::TensorList out) { + return at::_ops::_foreach_pow_Scalar_out::call(self, exponent, out); +} + +// aten::_foreach_pow.ScalarList_out(Tensor[] self, Scalar[] exponent, *, Tensor(a!)[] out) -> () +inline void _foreach_pow_out(at::TensorList out, at::TensorList self, at::ArrayRef exponent) { + return at::_ops::_foreach_pow_ScalarList_out::call(self, exponent, out); +} +// aten::_foreach_pow.ScalarList_out(Tensor[] self, Scalar[] exponent, *, Tensor(a!)[] out) -> () +inline void _foreach_pow_outf(at::TensorList self, at::ArrayRef exponent, at::TensorList out) { + return at::_ops::_foreach_pow_ScalarList_out::call(self, exponent, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4e391f75860162082c774c42741a3fe2e6c8469b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_compositeexplicitautograd_dispatch.h @@ -0,0 +1,40 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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_pow(at::TensorList self, at::TensorList exponent); +TORCH_API void _foreach_pow_out(at::TensorList out, at::TensorList self, at::TensorList exponent); +TORCH_API void _foreach_pow_outf(at::TensorList self, at::TensorList exponent, at::TensorList out); +TORCH_API void _foreach_pow_(at::TensorList self, at::TensorList exponent); +TORCH_API ::std::vector _foreach_pow(at::TensorList self, const at::Scalar & exponent); +TORCH_API void _foreach_pow_out(at::TensorList out, at::TensorList self, const at::Scalar & exponent); +TORCH_API void _foreach_pow_outf(at::TensorList self, const at::Scalar & exponent, at::TensorList out); +TORCH_API void _foreach_pow_(at::TensorList self, const at::Scalar & exponent); +TORCH_API ::std::vector _foreach_pow(at::TensorList self, at::ArrayRef exponent); +TORCH_API void _foreach_pow_out(at::TensorList out, at::TensorList self, at::ArrayRef exponent); +TORCH_API void _foreach_pow_outf(at::TensorList self, at::ArrayRef exponent, at::TensorList out); +TORCH_API void _foreach_pow_(at::TensorList self, at::ArrayRef exponent); +TORCH_API ::std::vector _foreach_pow(const at::Scalar & self, at::TensorList exponent); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..468ca3f592d7e45203d2ceecd9a11551855e289a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_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 ::std::vector _foreach_pow(at::TensorList self, at::TensorList exponent); +TORCH_API void _foreach_pow_(at::TensorList self, at::TensorList exponent); +TORCH_API ::std::vector _foreach_pow(at::TensorList self, const at::Scalar & exponent); +TORCH_API void _foreach_pow_(at::TensorList self, const at::Scalar & exponent); +TORCH_API ::std::vector _foreach_pow(at::TensorList self, at::ArrayRef exponent); +TORCH_API void _foreach_pow_(at::TensorList self, at::ArrayRef exponent); +TORCH_API ::std::vector _foreach_pow(const at::Scalar & self, at::TensorList exponent); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_native.h new file mode 100644 index 0000000000000000000000000000000000000000..71de7b8363eea06a9aecafe776d42296984a9492 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_native.h @@ -0,0 +1,42 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @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_pow_list_kernel_slow(at::TensorList self, at::TensorList exponent); +TORCH_API void _foreach_pow_List_out(at::TensorList self, at::TensorList exponent, at::TensorList out); +TORCH_API void foreach_tensor_pow_list_kernel_slow_(at::TensorList self, at::TensorList exponent); +TORCH_API ::std::vector foreach_tensor_pow_list_kernel_cuda(at::TensorList self, at::TensorList exponent); +TORCH_API void foreach_tensor_pow_list_kernel_cuda_(at::TensorList self, at::TensorList exponent); +TORCH_API ::std::vector foreach_tensor_pow_scalar_kernel_slow(at::TensorList self, const at::Scalar & exponent); +TORCH_API void _foreach_pow_Scalar_out(at::TensorList self, const at::Scalar & exponent, at::TensorList out); +TORCH_API void foreach_tensor_pow_scalar_kernel_slow_(at::TensorList self, const at::Scalar & exponent); +TORCH_API ::std::vector foreach_tensor_pow_scalar_kernel_cuda(at::TensorList self, const at::Scalar & exponent); +TORCH_API void foreach_tensor_pow_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & exponent); +TORCH_API ::std::vector foreach_tensor_pow_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef exponent); +TORCH_API void _foreach_pow_ScalarList_out(at::TensorList self, at::ArrayRef exponent, at::TensorList out); +TORCH_API void foreach_tensor_pow_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef exponent); +TORCH_API ::std::vector foreach_tensor_pow_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef exponent); +TORCH_API void foreach_tensor_pow_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef exponent); +TORCH_API ::std::vector foreach_scalar_pow_list_kernel_slow(const at::Scalar & self, at::TensorList exponent); +TORCH_API ::std::vector foreach_scalar_pow_list_kernel_cuda(const at::Scalar & self, at::TensorList exponent); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..afdbc921bb346f82ccbd927a0432df369dc56f37 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_pow_ops.h @@ -0,0 +1,133 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will 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_pow_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_pow"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_pow.List(Tensor[] self, Tensor[] exponent) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList exponent); +}; + +struct TORCH_API _foreach_pow_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_pow"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_pow.Scalar(Tensor[] self, Scalar exponent) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & exponent); +}; + +struct TORCH_API _foreach_pow_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_pow"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_pow.ScalarList(Tensor[] self, Scalar[] exponent) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef exponent); +}; + +struct TORCH_API _foreach_pow_ScalarAndTensor { + using schema = ::std::vector (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_pow"; + static constexpr const char* overload_name = "ScalarAndTensor"; + static constexpr const char* schema_str = "_foreach_pow.ScalarAndTensor(Scalar self, Tensor[] exponent) -> Tensor[]"; + static ::std::vector call(const at::Scalar & self, at::TensorList exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, at::TensorList exponent); +}; + +struct TORCH_API _foreach_pow__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_pow_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_pow_.List(Tensor(a!)[] self, Tensor[] exponent) -> ()"; + static void call(at::TensorList self, at::TensorList exponent); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList exponent); +}; + +struct TORCH_API _foreach_pow__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_pow_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_pow_.Scalar(Tensor(a!)[] self, Scalar exponent) -> ()"; + static void call(at::TensorList self, const at::Scalar & exponent); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & exponent); +}; + +struct TORCH_API _foreach_pow__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_pow_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_pow_.ScalarList(Tensor(a!)[] self, Scalar[] exponent) -> ()"; + static void call(at::TensorList self, at::ArrayRef exponent); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef exponent); +}; + +struct TORCH_API _foreach_pow_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_pow"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_pow.List_out(Tensor[] self, Tensor[] exponent, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList exponent, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList exponent, at::TensorList out); +}; + +struct TORCH_API _foreach_pow_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_pow"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_pow.Scalar_out(Tensor[] self, Scalar exponent, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & exponent, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & exponent, at::TensorList out); +}; + +struct TORCH_API _foreach_pow_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_pow"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_pow.ScalarList_out(Tensor[] self, Scalar[] exponent, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef exponent, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef exponent, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal.h new file mode 100644 index 0000000000000000000000000000000000000000..f3aaa6d2ee628419a5a51099d8e8ff6dc1351bc6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal.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_reciprocal(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_reciprocal(at::TensorList self) { + return at::_ops::_foreach_reciprocal::call(self); +} + +// aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () +inline void _foreach_reciprocal_(at::TensorList self) { + return at::_ops::_foreach_reciprocal_::call(self); +} + +// aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_reciprocal_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_reciprocal_out::call(self, out); +} +// aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_reciprocal_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_reciprocal_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ab7cc3bf5f08125c5d4fa99b674f9edd57295a28 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_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_reciprocal(at::TensorList self); +TORCH_API void _foreach_reciprocal_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_reciprocal_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_reciprocal_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..09c9336e306177f39b7a2f7e0fdf21c362704502 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_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_reciprocal(at::TensorList self); +TORCH_API void _foreach_reciprocal_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b70fb99d30c41b7e105ff9937629f94ff2044832 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_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_reciprocal_slow(at::TensorList self); +TORCH_API void _foreach_reciprocal_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_reciprocal_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_reciprocal_cuda(at::TensorList self); +TORCH_API void foreach_tensor_reciprocal_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1c45183ed06e94633ed342e36771685b3db53537 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_reciprocal { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_reciprocal"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_reciprocal(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_reciprocal_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_reciprocal_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_reciprocal_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_reciprocal_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_reciprocal"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round.h new file mode 100644 index 0000000000000000000000000000000000000000..60fd51d3d981c4314cc1184e011320956c65c145 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba5c455767ba3bf8c08344f7a8033996041cab91 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_round(at::TensorList self); +TORCH_API void _foreach_round_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_round_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_round_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c3b0a66a2b396fac9a836926241e6e98ab24c2c0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_round(at::TensorList self); +TORCH_API void _foreach_round_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e706199c9932dacd49ce6eea83e21d5aa5764c87 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_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_round_slow(at::TensorList self); +TORCH_API void _foreach_round_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_round_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_round_cuda(at::TensorList self); +TORCH_API void foreach_tensor_round_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bc84887e27e0c66488596c7649126f1856788030 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_round_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_round { + 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_round"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_round(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_round_ { + 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_round_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_round_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_round_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_round"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_round.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt.h new file mode 100644 index 0000000000000000000000000000000000000000..6733268c2128ee88996071c80b45561b048ec625 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt.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_rsqrt(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_rsqrt(at::TensorList self) { + return at::_ops::_foreach_rsqrt::call(self); +} + +// aten::_foreach_rsqrt_(Tensor(a!)[] self) -> () +inline void _foreach_rsqrt_(at::TensorList self) { + return at::_ops::_foreach_rsqrt_::call(self); +} + +// aten::_foreach_rsqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_rsqrt_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_rsqrt_out::call(self, out); +} +// aten::_foreach_rsqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_rsqrt_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_rsqrt_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d93226a670962d88aeeddf61dfd93e28fbef2fa --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_rsqrt(at::TensorList self); +TORCH_API void _foreach_rsqrt_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_rsqrt_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_rsqrt_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ef3058248b2fe7dace813063e4f6f83dee8a87c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_rsqrt(at::TensorList self); +TORCH_API void _foreach_rsqrt_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_native.h new file mode 100644 index 0000000000000000000000000000000000000000..33420e00b4c431836d62931479795464fe7180eb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3af9a94f1e67946cd32e0b0f08adb5999a447a10 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_rsqrt_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_rsqrt { + 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_rsqrt"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_rsqrt(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_rsqrt_ { + 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_rsqrt_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_rsqrt_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_rsqrt_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_rsqrt"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_rsqrt.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid.h new file mode 100644 index 0000000000000000000000000000000000000000..79cbae7bcd8808cddecd91e6692b9f6580d5c6bb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid.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_sigmoid(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_sigmoid(at::TensorList self) { + return at::_ops::_foreach_sigmoid::call(self); +} + +// aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () +inline void _foreach_sigmoid_(at::TensorList self) { + return at::_ops::_foreach_sigmoid_::call(self); +} + +// aten::_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sigmoid_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_sigmoid_out::call(self, out); +} +// aten::_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sigmoid_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_sigmoid_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..21b5a2e0a8a88061e354cc3be3c35652411ad506 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_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_sigmoid(at::TensorList self); +TORCH_API void _foreach_sigmoid_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_sigmoid_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_sigmoid_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e1e43d3fa41c64c986883aad3a441ad73837e85 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_sigmoid(at::TensorList self); +TORCH_API void _foreach_sigmoid_(at::TensorList self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3b84c997bb417a6c5ed2bdb38997ad76bb18a3e7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_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_sigmoid_slow(at::TensorList self); +TORCH_API void _foreach_sigmoid_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sigmoid_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sigmoid_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sigmoid_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..58b3498ddcd7b476c2ee3732c7d72ed2dc60dad0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sigmoid_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_sigmoid { + 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_sigmoid"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sigmoid(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sigmoid_ { + 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_sigmoid_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sigmoid_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sigmoid_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_sigmoid"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sigmoid.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign.h new file mode 100644 index 0000000000000000000000000000000000000000..1fd3f35b68364bc5095a43d27e3f76b2f311134d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign.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_sign(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_sign(at::TensorList self) { + return at::_ops::_foreach_sign::call(self); +} + +// aten::_foreach_sign_(Tensor(a!)[] self) -> () +inline void _foreach_sign_(at::TensorList self) { + return at::_ops::_foreach_sign_::call(self); +} + +// aten::_foreach_sign.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sign_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_sign_out::call(self, out); +} +// aten::_foreach_sign.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sign_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2bf4590e7cce3190f772f739e2c0c4c21d352ee9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_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_sign(at::TensorList self); +TORCH_API void _foreach_sign_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_sign_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_sign_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4f979d53f22ef53d3852b127b72a87ab66afc559 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_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_sign(at::TensorList self); +TORCH_API void _foreach_sign_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b1e28df9f18f28096eccfeb64cb88b71e10bb6c4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_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_sign_slow(at::TensorList self); +TORCH_API void _foreach_sign_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sign_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sign_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sign_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..efd831a7790ea7234e2a505dbca8afe845f86642 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sign_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_sign { + 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_sign"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sign(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sign_ { + 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_sign_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sign_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sign_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_sign"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sign.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin.h new file mode 100644 index 0000000000000000000000000000000000000000..83e900336d3a55a36159c39bb8fd51e6c3af7053 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin.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_sin(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_sin(at::TensorList self) { + return at::_ops::_foreach_sin::call(self); +} + +// aten::_foreach_sin_(Tensor(a!)[] self) -> () +inline void _foreach_sin_(at::TensorList self) { + return at::_ops::_foreach_sin_::call(self); +} + +// aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sin_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_sin_out::call(self, out); +} +// aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sin_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_sin_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44b360459f26fcb6f4e45b64889e396e2b780b87 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_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_sin(at::TensorList self); +TORCH_API void _foreach_sin_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_sin_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_sin_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..158359447f6fb965c11ffa7be101831ed32b7ad7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_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_sin(at::TensorList self); +TORCH_API void _foreach_sin_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..33756f25f95e96b6e27f5204d19f39a4ed571fe1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_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_sin_slow(at::TensorList self); +TORCH_API void _foreach_sin_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sin_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sin_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sin_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..926d21ee0a837f48b7e3876bb64d4fcb068607a4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sin_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_sin { + 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_sin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sin(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sin_ { + 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_sin_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sin_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sin_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_sin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sin.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh.h new file mode 100644 index 0000000000000000000000000000000000000000..b417d5e260b666be35d667873c6c2268752f931c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_sinh(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_sinh(at::TensorList self) { + return at::_ops::_foreach_sinh::call(self); +} + +// aten::_foreach_sinh_(Tensor(a!)[] self) -> () +inline void _foreach_sinh_(at::TensorList self) { + return at::_ops::_foreach_sinh_::call(self); +} + +// aten::_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sinh_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_sinh_out::call(self, out); +} +// aten::_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sinh_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_sinh_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..58bbccfa35dd30b010320732a49af6284d3dba34 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_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_sinh(at::TensorList self); +TORCH_API void _foreach_sinh_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_sinh_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_sinh_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e57f1820345b24a181a0dc246db82e344602136 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_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_sinh(at::TensorList self); +TORCH_API void _foreach_sinh_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fb976f1731e41f605c3e881389ce9c3d526a842c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_sinh_slow(at::TensorList self); +TORCH_API void _foreach_sinh_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sinh_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sinh_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sinh_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..131eef59901ed84b80f182be8de4c3a2d98106df --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_sinh { + 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_sinh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sinh(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sinh_ { + 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_sinh_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sinh_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sinh_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_sinh"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sinh.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt.h new file mode 100644 index 0000000000000000000000000000000000000000..af18c26757164597707f48a4051751b5a2ca0036 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt.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_sqrt(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_sqrt(at::TensorList self) { + return at::_ops::_foreach_sqrt::call(self); +} + +// aten::_foreach_sqrt_(Tensor(a!)[] self) -> () +inline void _foreach_sqrt_(at::TensorList self) { + return at::_ops::_foreach_sqrt_::call(self); +} + +// aten::_foreach_sqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sqrt_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_sqrt_out::call(self, out); +} +// aten::_foreach_sqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sqrt_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_sqrt_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cec9f2125109bc25555fb550dde41f1ae0c4c337 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_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_sqrt(at::TensorList self); +TORCH_API void _foreach_sqrt_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_sqrt_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_sqrt_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e33f24d62fceb83e4f9193dc3676ad6a8372a760 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_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_sqrt(at::TensorList self); +TORCH_API void _foreach_sqrt_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6a15fca466e40709aebb8a4fb4223120601034be --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_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_sqrt_slow(at::TensorList self); +TORCH_API void _foreach_sqrt_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sqrt_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sqrt_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sqrt_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2902e03fb14a081c60b4000b316487007f77431a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_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_sqrt { + 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_sqrt"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sqrt(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sqrt_ { + 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_sqrt_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sqrt_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sqrt_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_sqrt"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sqrt.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub.h new file mode 100644 index 0000000000000000000000000000000000000000..9662e249a76ff8d3e090023618d08264835132d8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub.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_sub.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_sub(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_sub_Scalar::call(self, scalar); +} + +// aten::_foreach_sub_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_sub_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_sub__Scalar::call(self, scalar); +} + +// aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] +inline ::std::vector _foreach_sub(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_sub_List::call(self, other, alpha); +} + +// aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () +inline void _foreach_sub_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_sub__List::call(self, other, alpha); +} + +// aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_sub(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_sub_ScalarList::call(self, scalars); +} + +// aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_sub_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_sub__ScalarList::call(self, scalars); +} + +// aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_sub_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_sub_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_sub_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_sub_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_sub_out(at::TensorList out, at::TensorList self, at::TensorList other, const at::Scalar & alpha=1) { + return at::_ops::_foreach_sub_List_out::call(self, other, alpha, out); +} +// aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () +inline void _foreach_sub_outf(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out) { + return at::_ops::_foreach_sub_List_out::call(self, other, alpha, out); +} + +// aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_sub_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_sub_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_sub_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_sub_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf6a2df89b6060e85f0ad90bbae7652de00dedb5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_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_sub(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_sub_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_sub_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_sub_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_sub(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_sub_out(at::TensorList out, at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_sub_outf(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +TORCH_API void _foreach_sub_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector _foreach_sub(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_sub_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_sub_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_sub_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..499adac91d8e33cb8e31ad59799625b01a2e091e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_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::vector _foreach_sub(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_sub_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_sub(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_sub_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector _foreach_sub(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_sub_(at::TensorList self, at::ArrayRef scalars); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_native.h new file mode 100644 index 0000000000000000000000000000000000000000..97d3e5110c45dd08f6bf5c1033dd393aaf8a799a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..309e4e16a89d9431a21db3ce73923d8b947ce90f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h @@ -0,0 +1,122 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_sub_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_sub.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_sub__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_sub_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_sub_List { + using schema = ::std::vector (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_sub__List { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> ()"; + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_sub_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_sub__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_sub_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_sub_List_out { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +}; + +struct TORCH_API _foreach_sub_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sub"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan.h new file mode 100644 index 0000000000000000000000000000000000000000..985b48ac272d678734e51ed2a89bda5de6747c3f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_tan(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_tan(at::TensorList self) { + return at::_ops::_foreach_tan::call(self); +} + +// aten::_foreach_tan_(Tensor(a!)[] self) -> () +inline void _foreach_tan_(at::TensorList self) { + return at::_ops::_foreach_tan_::call(self); +} + +// aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tan_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_tan_out::call(self, out); +} +// aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tan_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_tan_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c0ffd1f66bb56be934f0a4e394690da6d17d90b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_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_tan(at::TensorList self); +TORCH_API void _foreach_tan_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_tan_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_tan_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c295ccef4a8c9db3ccd69ec3650dea57a3278620 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_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_tan(at::TensorList self); +TORCH_API void _foreach_tan_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2783a3081423f80ae653f57c42a5c6b37a83a4ef --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_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_tan_slow(at::TensorList self); +TORCH_API void _foreach_tan_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_tan_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_tan_cuda(at::TensorList self); +TORCH_API void foreach_tensor_tan_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c44d06063e0127ddb5eb6b5c521840f4484ec503 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tan_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_tan { + 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_tan"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_tan(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_tan_ { + 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_tan_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_tan_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_tan_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_tan"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_tan.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh.h new file mode 100644 index 0000000000000000000000000000000000000000..64d39aea5ceae758ba9a7807c933f164f6e0ca23 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_tanh(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_tanh(at::TensorList self) { + return at::_ops::_foreach_tanh::call(self); +} + +// aten::_foreach_tanh_(Tensor(a!)[] self) -> () +inline void _foreach_tanh_(at::TensorList self) { + return at::_ops::_foreach_tanh_::call(self); +} + +// aten::_foreach_tanh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tanh_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_tanh_out::call(self, out); +} +// aten::_foreach_tanh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tanh_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_tanh_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..40cfc75af33913967edce9e26336f5e0ed4a838e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02930b3ab45a704a44825a4ac0f2993f45075010 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_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_tanh(at::TensorList self); +TORCH_API void _foreach_tanh_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0c53e23052a30d2cab12eac099f9149d38644aee --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_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_tanh_slow(at::TensorList self); +TORCH_API void _foreach_tanh_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_tanh_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_tanh_cuda(at::TensorList self); +TORCH_API void foreach_tensor_tanh_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e693b18d0efdc85967daffa577f70f7404e419a5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_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_tanh { + 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_tanh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_tanh(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_tanh_ { + 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_tanh_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_tanh_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_tanh_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_tanh"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_tanh.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc.h new file mode 100644 index 0000000000000000000000000000000000000000..d19d6cbd377d23ff595f98beaa109dc7387d7ee1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc.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_trunc(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_trunc(at::TensorList self) { + return at::_ops::_foreach_trunc::call(self); +} + +// aten::_foreach_trunc_(Tensor(a!)[] self) -> () +inline void _foreach_trunc_(at::TensorList self) { + return at::_ops::_foreach_trunc_::call(self); +} + +// aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_trunc_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_trunc_out::call(self, out); +} +// aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_trunc_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_trunc_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7fefa16bb64374f5b526d0463b54762f4ee1b0d7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_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_trunc(at::TensorList self); +TORCH_API void _foreach_trunc_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_trunc_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_trunc_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2527215f3baed6884828b17e92f70497f23b2e73 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_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_trunc(at::TensorList self); +TORCH_API void _foreach_trunc_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7ab6bbd7ad4a0cb1d17f73cd31be91ce96df0944 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_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_trunc_slow(at::TensorList self); +TORCH_API void _foreach_trunc_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_trunc_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_trunc_cuda(at::TensorList self); +TORCH_API void foreach_tensor_trunc_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6e8149d260c81a900b2dcb1a89f15873647bee51 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_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 _foreach_trunc { + 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_trunc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_trunc(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_trunc_ { + 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_trunc_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_trunc_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_trunc_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_trunc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_trunc.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero.h new file mode 100644 index 0000000000000000000000000000000000000000..8ce3d26eaeb0a77f29d20d336909064c835d0228 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_zero_(Tensor(a!)[] self) -> () +inline void _foreach_zero_(at::TensorList self) { + return at::_ops::_foreach_zero_::call(self); +} + +// aten::_foreach_zero.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_zero_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_zero_out::call(self, out); +} +// aten::_foreach_zero.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_zero_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_zero_out::call(self, out); +} + +// aten::_foreach_zero(Tensor[] self) -> Tensor[] self_out +inline ::std::vector _foreach_zero(at::TensorList self) { + return at::_ops::_foreach_zero::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9be73e5e4af26673687433475ff246c2bea037c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_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_zero(at::TensorList self); +TORCH_API void _foreach_zero_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_zero_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_zero_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce408fecc0a3972315119f2a338ce6a4a447f304 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API void _foreach_zero_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4a9e8127571513f42f07c63d30e193e2a771314f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector _foreach_zero(at::TensorList self); +TORCH_API void _foreach_zero_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_zero_slow_(at::TensorList self); +TORCH_API void foreach_tensor_zero_cuda_(at::TensorList self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0f88a0b25f8503f28d0e564b2689c8e505f7294d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_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_zero_ { + 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_zero_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_zero_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_zero_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_zero"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_zero.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); +}; + +struct TORCH_API _foreach_zero { + 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_zero"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_zero(Tensor[] self) -> Tensor[] self_out"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async.h new file mode 100644 index 0000000000000000000000000000000000000000..85f6b8dd508f68593a37fd2048bad18b8a69ad7b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async.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_assert_async.msg(Tensor self, str assert_msg, Tensor dep_token) -> Tensor +inline at::Tensor _functional_assert_async(const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token) { + return at::_ops::_functional_assert_async_msg::call(self, assert_msg, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..68b2c9a4b09367a646aedeb3b1de41de5958cca2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_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 _functional_assert_async(const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_native.h new file mode 100644 index 0000000000000000000000000000000000000000..396406e74d4c64ae0201b7d928fa6b3afa2fcfae --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _functional_assert_async_msg_cpu(const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ad4e53e4898b97553362eef909aa89ce236a34ce --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_async_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _functional_assert_async_msg { + using schema = at::Tensor (const at::Tensor &, c10::string_view, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_functional_assert_async"; + static constexpr const char* overload_name = "msg"; + static constexpr const char* schema_str = "_functional_assert_async.msg(Tensor self, str assert_msg, Tensor dep_token) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar.h new file mode 100644 index 0000000000000000000000000000000000000000..0166eb7ebb9f3dbacad263df812f11d5b88eed6b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar.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_assert_scalar(Scalar self, str assert_msg, Tensor dep_token) -> Tensor +inline at::Tensor _functional_assert_scalar(const at::Scalar & self, c10::string_view assert_msg, const at::Tensor & dep_token) { + return at::_ops::_functional_assert_scalar::call(self, assert_msg, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd4d5788b32de528c3fec6da0691aafda842c595 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b043faee8618cd4873bbf2dec283d7a6e2322da3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _functional_assert_scalar(const at::Scalar & self, c10::string_view assert_msg, const at::Tensor & dep_token); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..56e14640303085e56a68e3967d31a066ea577c24 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_assert_scalar_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _functional_assert_scalar { + using schema = at::Tensor (const at::Scalar &, c10::string_view, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_functional_assert_scalar"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_functional_assert_scalar(Scalar self, str assert_msg, Tensor dep_token) -> Tensor"; + static at::Tensor call(const at::Scalar & self, c10::string_view assert_msg, const at::Tensor & dep_token); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, c10::string_view assert_msg, const at::Tensor & dep_token); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range.h new file mode 100644 index 0000000000000000000000000000000000000000..25a0d03daf903021bb5f23bc2821dae88c866353 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0ae26b5083d64fd1dbf2a2f86dbde7df6d4fb8a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_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_sym_constrain_range(const at::Scalar & size, ::std::optional min, ::std::optional max, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size.h new file mode 100644 index 0000000000000000000000000000000000000000..7b3749c7bec7fef256fbff4d2cc972e6c4458dbe --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_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::_functional_sym_constrain_range_for_size(Scalar size, int? min, int? max, Tensor dep_token) -> Tensor +inline at::Tensor _functional_sym_constrain_range_for_size(const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token) { + return at::_ops::_functional_sym_constrain_range_for_size::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3675c774c36436b7fe8181829d24efca2333e187 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _functional_sym_constrain_range_for_size(const at::Scalar & size, ::std::optional min, ::std::optional max, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7da4ed2a110304d8798264caaaf37a254565073c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1af5d09c4e152720cb81533a7219875cba743ef2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_for_size_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _functional_sym_constrain_range_for_size { + using schema = at::Tensor (const at::Scalar &, ::std::optional, ::std::optional, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_functional_sym_constrain_range_for_size"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_functional_sym_constrain_range_for_size(Scalar size, int? min, int? max, Tensor dep_token) -> Tensor"; + static at::Tensor call(const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1cd10660ced37c9da28bb9a564ef3ce5f08a9105 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_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(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..88e99aa666d5abcac9067d5a9cbb469c366a21af --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _functional_sym_constrain_range { + using schema = at::Tensor (const at::Scalar &, ::std::optional, ::std::optional, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_functional_sym_constrain_range"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_functional_sym_constrain_range(Scalar size, int? min, int? max, Tensor dep_token) -> Tensor"; + static at::Tensor call(const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad.h new file mode 100644 index 0000000000000000000000000000000000000000..d21f9bf639992cfca76c45bac8a1fec3e70654cf --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad.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_adagrad_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline 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={}) { + return at::_ops::_fused_adagrad_::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf); +} + +// aten::_fused_adagrad_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline 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={}) { + return at::_ops::_fused_adagrad__tensor_lr::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf); +} + +// aten::_fused_adagrad.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adagrad_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adagrad_out::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adagrad.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adagrad_outf(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adagrad_out::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adagrad(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out, Tensor[] state_steps_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adagrad::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf); +} + +// aten::_fused_adagrad.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adagrad_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adagrad_tensor_lr_out::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adagrad.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adagrad_outf(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adagrad_tensor_lr_out::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adagrad.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adagrad_tensor_lr::call(self, grads, state_sums, state_steps, lr, lr_decay, weight_decay, eps, maximize, grad_scale, found_inf); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a5c2aa2047b353c390c7af7df7643003121d1637 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_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> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_outf(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_outf(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2ef2858958b0910b7c7b111e4793682d311d9399 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_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 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 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5abec11601627067d6f4eda53ed3edf0d0b9c6e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9ec0f048e8e2592caf970d4c5b5f1f645a0dbe4e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_out(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API void _fused_adagrad_kernel_cpu_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_kernel_cuda_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_tensor_lr_out(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API void _fused_adagrad_kernel_cpu_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_kernel_cuda_(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c405f213414bac9f4314d7e0e135bd7cb1715841 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_adagrad_ { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adagrad_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad__tensor_lr { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad_"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adagrad_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fused_adagrad.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +}; + +struct TORCH_API _fused_adagrad { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adagrad(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out, Tensor[] state_steps_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad_tensor_lr_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = "tensor_lr_out"; + static constexpr const char* schema_str = "_fused_adagrad.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +}; + +struct TORCH_API _fused_adagrad_tensor_lr { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adagrad"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adagrad.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, Tensor lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector> call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static ::std::tuple<::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, const at::Tensor & lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam.h new file mode 100644 index 0000000000000000000000000000000000000000..03d86e4830c1ad464d26af6fb45e4cf87e30746c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam.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_adam_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_adam_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adam_::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adam_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_adam_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adam__tensor_lr::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adam_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adam_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adam_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adam_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adam(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adam(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adam::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adam.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adam_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adam_tensor_lr_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adam.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adam_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adam_tensor_lr_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adam.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adam(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adam_tensor_lr::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a01e28aa7af0ae10445007c5c86f0a143e57483 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_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_adam(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_adam_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_adam_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_adam(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_adam_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_adam_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9256568a0ebfbeadca7b3d28c19a1d39155721ed --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_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 void _fused_adam_(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_adam_(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 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..76cde475f356cb58d20113d1cf5c0aa023afa930 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_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_adam_(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_adam_(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1feaf933da305c6f0e93f7873722a2fe34fb37c5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_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_adam(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_adam_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_adam_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_adam_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_adam(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_adam_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_adam_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_adam_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5fe4c1d6e5190bbde2dd4e683c2286631c99ea99 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adam_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_adam_ { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adam_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adam_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adam__tensor_lr { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adam_"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adam_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adam_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adam"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adam { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adam"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adam(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> call(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); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adam_tensor_lr_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adam"; + static constexpr const char* overload_name = "tensor_lr_out"; + static constexpr const char* schema_str = "_fused_adam.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adam_tensor_lr { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adam"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adam.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> call(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); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, 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 at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw.h new file mode 100644 index 0000000000000000000000000000000000000000..a61f027619b2a91c9a90bebfbd66b9b17fa6b757 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw.h @@ -0,0 +1,69 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_adamw_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adamw_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () +inline void _fused_adamw_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw__tensor_lr::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adamw_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adamw(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +// aten::_fused_adamw.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_tensor_lr_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} +// aten::_fused_adamw.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () +inline void _fused_adamw_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out) { + return at::_ops::_fused_adamw_tensor_lr_out::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); +} + +// aten::_fused_adamw.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) +inline ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adamw(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}) { + return at::_ops::_fused_adamw_tensor_lr::call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04b8be9f3b72af3e65c659f31e373f4d5d0e1f2b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..af7a618f88db53caf90039292ec8dfbb9245b8f1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_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 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 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6be1e402c148ca2099a1f22bd36e020587cff212 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d0d998544b51e588a2a273986cb720213bbfeeed --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3c6a74202cd5424e1c79db0d7e74caca5dc7f268 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_adamw_ { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adamw_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adamw__tensor_lr { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adamw_"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adamw_.tensor_lr(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adamw_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adamw"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adamw { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adamw"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> call(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); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adamw_tensor_lr_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adamw"; + static constexpr const char* overload_name = "tensor_lr_out"; + static constexpr const char* schema_str = "_fused_adamw.tensor_lr_out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_adamw_tensor_lr { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, double, double, double, double, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_adamw"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_fused_adamw.tensor_lr(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, Tensor lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> call(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); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, 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 at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..dc6b1dd6b1e18916badae283c90a4a92c4bd0b36 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor) +inline ::std::tuple _fused_dropout(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::_fused_dropout::call(self, p, generator); +} + +// aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fused_dropout_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::_fused_dropout_out::call(self, p, generator, out0, out1); +} +// aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fused_dropout_outf(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_fused_dropout_out::call(self, p, generator, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c4f8f63af664dc3a70bd64f511eed288211ab042 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..62420cff88df9ca0dc17b426ef8ba89ef9aabcc5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_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 _fused_dropout(const at::Tensor & self, double p, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eef55b71093157cfe20178dfcd977fa016c6b344 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_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 ::std::tuple _fused_dropout_out(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple fused_dropout_cuda(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b8edfbba146a5511959be2ac49d0e24f72e26293 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_dropout { + using schema = ::std::tuple (const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_dropout"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, double p, ::std::optional generator); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional generator); +}; + +struct TORCH_API _fused_dropout_out { + using schema = ::std::tuple (const at::Tensor &, double, ::std::optional, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_dropout"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional generator, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..b7554bb65609d1340ec75710f61c5d8354f64287 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e3018bd470346eef3e096e0a2309979945e2ce3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_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 ::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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad1e164514a86c3cca7907df42f9092e0d9c99ab --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::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); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_native.h new file mode 100644 index 0000000000000000000000000000000000000000..88eb38ecbf89714d19c7121d07c564a0a1596082 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_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 _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(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); +TORCH_API ::std::tuple fused_moving_avg_obs_fake_quant_cpu(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_fake_quant_cuda(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1e3364015a9cd8ba82c928cc433fe8a8b0de1af --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..ffb19316bb1b2370606e45a982083caf56a7082a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_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::_fused_rms_norm(Tensor input, int[] normalized_shape, Tensor? weight, float? eps) -> (Tensor, Tensor) +inline ::std::tuple _fused_rms_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional eps) { + return at::_ops::_fused_rms_norm::call(input, normalized_shape, weight, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..e68188a1597dfb196f85ed77c5bf054674217adb --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fused_rms_norm_backward(Tensor grad_out, Tensor input, int[] normalized_shape, Tensor rstd, Tensor? weight, bool[2] output_mask) -> (Tensor, Tensor) +inline ::std::tuple _fused_rms_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & rstd, const ::std::optional & weight, ::std::array output_mask) { + return at::_ops::_fused_rms_norm_backward::call(grad_out, input, normalized_shape, rstd, weight, output_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3add70e853927d8d9e80cecba4d68a5942489d00 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_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 _fused_rms_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & rstd, const ::std::optional & weight, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7e82a8d1315e29aa2450793e5de14442d79f44a5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_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 _fused_rms_norm_backward_cuda(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & rstd, const ::std::optional & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5b2a3982a816be271f8d8ebaea01309676a79a22 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_rms_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const at::Tensor &, const ::std::optional &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_rms_norm_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_rms_norm_backward(Tensor grad_out, Tensor input, int[] normalized_shape, Tensor rstd, Tensor? weight, bool[2] output_mask) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & rstd, const ::std::optional & weight, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & rstd, const ::std::optional & weight, ::std::array output_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aae265c327aa2d402f0554fe258b902360823325 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_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 ::std::tuple _fused_rms_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional eps); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b59c23785a6d0a74a2068b81a5d9e5cd86db404 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_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 _fused_rms_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional eps); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ac50ccafb87145aeda129c331891f7b81a933d7f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_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 rms_norm_composite(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional eps); +TORCH_API ::std::tuple _fused_rms_norm_cuda(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b3527081abcb1bcc9e23b8902f2678ab79c34367 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_rms_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 _fused_rms_norm { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, const ::std::optional &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_rms_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_rms_norm(Tensor input, int[] normalized_shape, Tensor? weight, float? eps) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional eps); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, ::std::optional eps); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice.h new file mode 100644 index 0000000000000000000000000000000000000000..dfc4ae50e486450db87a0ae828114780d97ff53e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice.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::_fused_sdp_choice(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None, bool enable_gqa=False) -> int +inline int64_t _fused_sdp_choice(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false) { + return at::_ops::_fused_sdp_choice::call(query, key, value, attn_mask, dropout_p, is_causal, scale, enable_gqa); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0d42c225a2ceda86df9415d9cf5924ff4f8bad3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API int64_t _fused_sdp_choice(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f77bdf0830c6e1b704362f650627793924828de6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_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 _fused_sdp_choice(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_meta_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02d3233cb1401769d7656da7e3ec5a04fe1a06b6 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_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 int64_t _fused_sdp_choice(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); + +} // namespace 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0e984df10a83ff976b7ff691878ad04835a813af --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_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 int64_t _fused_sdp_choice_cpp(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); +TORCH_API int64_t _fused_sdp_choice_cuda(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); +TORCH_API int64_t _fused_sdp_choice_meta(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5d60085bfbf93c2a54dd0b01fc7e627fb4b3d981 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sdp_choice_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 _fused_sdp_choice { + using schema = int64_t (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, double, bool, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sdp_choice"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fused_sdp_choice(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None, bool enable_gqa=False) -> int"; + static int64_t call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, ::std::optional scale, bool enable_gqa); + static int64_t 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, ::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd.h new file mode 100644 index 0000000000000000000000000000000000000000..730d1b8fb7395d274c380ed3e005029f60b1cab3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb798e1fe01ec608a9d462b2c52bdc59e06df907 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8eb8d4cb87dc8ee88995e7dba29a006eba86219e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_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 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={}); +TORCH_API 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={}); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9c5eda107c207edb01da7a97dd45e734203825d3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_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_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_(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={}); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..69be06e0332ff58d9149a175356e8c6eb11155e4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_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> _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 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 void _fused_sgd_kernel_cpu_(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_kernel_cuda_(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 ::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_tensor_lr_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, at::TensorList out); +TORCH_API void _fused_sgd_kernel_cpu_(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_kernel_cuda_(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={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..104996f1248c3135b3f8acf435ade8358a14f379 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_sgd_ { + using schema = void (at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sgd_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_sgd__tensor_lr { + using schema = void (at::TensorList, at::TensorList, at::TensorList, double, double, const at::Tensor &, double, bool, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sgd_"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_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) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_sgd_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, bool, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sgd"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_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) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_sgd { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sgd"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector> call(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); + static ::std::tuple<::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_sgd_tensor_lr_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, double, double, const at::Tensor &, double, bool, bool, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sgd"; + static constexpr const char* overload_name = "tensor_lr_out"; + static constexpr const char* schema_str = "_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) -> ()"; + static void call(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); + static void redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fused_sgd_tensor_lr { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, double, double, const at::Tensor &, double, bool, bool, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fused_sgd"; + static constexpr const char* overload_name = "tensor_lr"; + static constexpr const char* schema_str = "_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)"; + static ::std::tuple<::std::vector,::std::vector,::std::vector> call(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); + static ::std::tuple<::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal.h new file mode 100644 index 0000000000000000000000000000000000000000..d9d94a50c53478d506395398a06a3f9b382fd7f1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal.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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..244f6241b23155b7b78f78dd2f54523f581ee251 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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 _fw_primal(const at::Tensor & self, int64_t level); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..7792cf0eeec7a615ae1a70fe8ee81404dff5c779 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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::_fw_primal_copy(Tensor self, int level) -> Tensor +inline at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level) { + return at::_ops::_fw_primal_copy::call(self, level); +} + +// aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fw_primal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t level) { + return at::_ops::_fw_primal_copy_out::call(self, level, out); +} +// aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fw_primal_copy_outf(const at::Tensor & self, int64_t level, at::Tensor & out) { + return at::_ops::_fw_primal_copy_out::call(self, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c952ad3b5af8c9d69705226fe50cf75ec93ca94 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _fw_primal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t level); +TORCH_API at::Tensor & _fw_primal_copy_outf(const at::Tensor & self, int64_t level, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9d22b2321f5cfe46517f5503e9e0ef77c18fc9e1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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 _fw_primal_copy(const at::Tensor & self, int64_t level); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..059f41911f3d55cc37b9b6d9da89c067d5985298 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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 & _fw_primal_copy_out(const at::Tensor & self, int64_t level, at::Tensor & out); +TORCH_API at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c5317f42cc9d679a3e91d3351e1d0d2b3fd68d38 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..67a5dd7e25bdbff4a8fcb3f56fc53c467e068adc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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 _fw_primal(const at::Tensor & self, int64_t level); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8a294abafa4537c004b816a0fda4adf48b0f009b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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 _fw_primal { + 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"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fw_primal(Tensor(a) self, int level) -> Tensor(a)"; + 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); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..546f4d5d26e95c65c06db250f7ec76f74d27fa3e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_gather_sparse_backward(Tensor self, int dim, Tensor index, Tensor grad) -> Tensor +inline at::Tensor _gather_sparse_backward(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad) { + return at::_ops::_gather_sparse_backward::call(self, dim, index, grad); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ed3ac994dffdd464de6abe90619dad858af9a8bf --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_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 _gather_sparse_backward(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8393df9dee2248d540eb77c90bc2ed9f2a82657f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _gather_sparse_backward(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..18af9037427c770eba149fca05a52590d997a0a5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _gather_sparse_backward { + 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::_gather_sparse_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_gather_sparse_backward(Tensor self, int dim, Tensor index, Tensor grad) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback.h new file mode 100644 index 0000000000000000000000000000000000000000..0d7d86e9acd120e64c700872759d8055341fb160 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_grid_sampler_2d_cpu_fallback(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor +inline at::Tensor _grid_sampler_2d_cpu_fallback(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::_grid_sampler_2d_cpu_fallback::call(input, grid, interpolation_mode, padding_mode, align_corners); +} + +// aten::_grid_sampler_2d_cpu_fallback.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _grid_sampler_2d_cpu_fallback_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::_grid_sampler_2d_cpu_fallback_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} +// aten::_grid_sampler_2d_cpu_fallback.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _grid_sampler_2d_cpu_fallback_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) { + return at::_ops::_grid_sampler_2d_cpu_fallback_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..f373fb86aa27d0a3edb824902cd452be9300cea1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_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::_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor) +inline ::std::tuple _grid_sampler_2d_cpu_fallback_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::_grid_sampler_2d_cpu_fallback_backward::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..96144cae319b0bede01ea0dbebc38fb9dd428cae --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple _grid_sampler_2d_cpu_fallback_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..68353e05715333e03fdbef227300a7abdd0dcd0b --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _grid_sampler_2d_cpu_fallback_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4891535d6ea13ae9d35c4346bc22398a44719b9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _grid_sampler_2d_cpu_fallback_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grid_sampler_2d_cpu_fallback_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aefc01a13fc3c20f09fa44eec8531f74090457e2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_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 _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(at::Tensor & out, 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_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eb484aa3d936a52c34da147a3a5eadc7bb2449ee --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..049e1e90786c0418ef6952bbca002f622e4a2407 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_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 _grid_sampler_2d_cpu_fallback { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grid_sampler_2d_cpu_fallback"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_grid_sampler_2d_cpu_fallback(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +}; + +struct TORCH_API _grid_sampler_2d_cpu_fallback_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grid_sampler_2d_cpu_fallback"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_grid_sampler_2d_cpu_fallback.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..aabe5a01302e1b23c0ce012e5c1a9f019e1418f5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_grouped_mm(Tensor self, Tensor mat2, Tensor? offs=None, Tensor? bias=None, ScalarType? out_dtype=None) -> Tensor +inline at::Tensor _grouped_mm(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt) { + return at::_ops::_grouped_mm::call(self, mat2, offs, bias, out_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f96534d3a34df27d9763dd75b9d7863ef2545760 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_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 _grouped_mm(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6d814108e192fd573e14d98d3b8881826e3582f2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_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 _grouped_mm(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8d31f98e372e127a36b66d2721a1d335e57834d2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _grouped_mm(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt); +TORCH_API at::Tensor _grouped_mm_cuda(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs={}, const ::std::optional & bias={}, ::std::optional out_dtype=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7b5085930c0d05d3019e250feec8a9dee5a07648 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_grouped_mm_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _grouped_mm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grouped_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_grouped_mm(Tensor self, Tensor mat2, Tensor? offs=None, Tensor? bias=None, ScalarType? out_dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs, const ::std::optional & bias, ::std::optional out_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, const ::std::optional & offs, const ::std::optional & bias, ::std::optional out_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type.h new file mode 100644 index 0000000000000000000000000000000000000000..fef3db047e4912ecc189db1c8524793584edd6a0 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_compositeimplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5afe88bbe083f467afefcd9f601f9ba5e51e8824 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_native.h new file mode 100644 index 0000000000000000000000000000000000000000..de7e07fff6da10fac02156c9a008a3225c2c5d53 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool _has_compatible_shallow_copy_type(const at::Tensor & self, const at::Tensor & from); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0c5467659e037beca65e47de47735d752c93058e --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_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 _has_compatible_shallow_copy_type { + 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::_has_compatible_shallow_copy_type"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_has_compatible_shallow_copy_type(Tensor self, Tensor from) -> bool"; + static bool call(const at::Tensor & self, const at::Tensor & from); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & from); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel.h new file mode 100644 index 0000000000000000000000000000000000000000..075f59e8e2dea94c0f73edeba36770e2c3ee0c83 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_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::_has_same_storage_numel(Tensor self, Tensor other) -> bool +inline bool _has_same_storage_numel(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::_has_same_storage_numel::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da42843b41e00c7b598c360a93fff8ec18ae5a76 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API bool _has_same_storage_numel(const at::Tensor & self, const at::Tensor & other); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h new file mode 100644 index 0000000000000000000000000000000000000000..20a0af13aa410409b21edd06aa631d3b4ff06510 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool _has_same_storage_numel(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8ca657a63340a5eab3d95f83771673eafe9de118 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_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 _has_same_storage_numel { + 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::_has_same_storage_numel"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_has_same_storage_numel(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges.h new file mode 100644 index 0000000000000000000000000000000000000000..7eb8c2fc007f69d8dd638038abe5ea263bed550d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges.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::_histogramdd_bin_edges(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor[] +inline ::std::vector _histogramdd_bin_edges(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_bin_edges::call(self, bins, range, weight, density); +} + +// aten::_histogramdd_bin_edges.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!)[] out) -> () +inline 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) { + return at::_ops::_histogramdd_bin_edges_out::call(self, bins, range, weight, density, out); +} +// aten::_histogramdd_bin_edges.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!)[] out) -> () +inline void _histogramdd_bin_edges_outf(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::TensorList out) { + return at::_ops::_histogramdd_bin_edges_out::call(self, bins, range, weight, density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..725d6adf13d2e66e6a532849448e749a88125d77 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ebbd414f8ae5436b41d69a36fa021bc9d7b5993 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_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::vector _histogramdd_bin_edges(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_native.h new file mode 100644 index 0000000000000000000000000000000000000000..df1d85cdd076a31b8d13eebb34b824e4ed763a06 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ad5e362a1bdbb0e94bc009490f43b1d7ceaf2ecc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_bin_edges_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 _histogramdd_bin_edges { + using schema = ::std::vector (const at::Tensor &, at::IntArrayRef, ::std::optional>, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_bin_edges"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_histogramdd_bin_edges(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor[]"; + static ::std::vector call(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density); +}; + +struct TORCH_API _histogramdd_bin_edges_out { + using schema = void (const at::Tensor &, at::IntArrayRef, ::std::optional>, const ::std::optional &, bool, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_bin_edges"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_histogramdd_bin_edges.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!)[] out) -> ()"; + static void call(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts.h new file mode 100644 index 0000000000000000000000000000000000000000..1a68d29ae65cbb479ad38bd4564244f2bf2990d1 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts.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::_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor +inline at::Tensor _histogramdd_from_bin_cts(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_from_bin_cts::call(self, bins, range, weight, density); +} + +// aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _histogramdd_from_bin_cts_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_from_bin_cts_out::call(self, bins, range, weight, density, out); +} +// aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _histogramdd_from_bin_cts_outf(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::Tensor & out) { + return at::_ops::_histogramdd_from_bin_cts_out::call(self, bins, range, weight, density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fc1a36dd822801b23f84456e2c916fca2b66e6e4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_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 & _histogramdd_from_bin_cts_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API at::Tensor & _histogramdd_from_bin_cts_outf(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..42af872f0954f02301992955c93659bae1b0ca4c --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_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 _histogramdd_from_bin_cts(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9938b46cf857828bc2a10ace5113a1176c30d425 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bf0232bad37a5b6619b2ff51795e07333ac85710 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_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 _histogramdd_from_bin_cts { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, ::std::optional>, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_from_bin_cts"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density); +}; + +struct TORCH_API _histogramdd_from_bin_cts_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, ::std::optional>, const ::std::optional &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_from_bin_cts"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors.h new file mode 100644 index 0000000000000000000000000000000000000000..72ab6e49f2aa5a12b59b45523806fa8cc4fb9fe4 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors.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::_histogramdd_from_bin_tensors(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False) -> Tensor +inline at::Tensor _histogramdd_from_bin_tensors(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_from_bin_tensors::call(self, bins, weight, density); +} + +// aten::_histogramdd_from_bin_tensors.out(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _histogramdd_from_bin_tensors_out(at::Tensor & out, const at::Tensor & self, at::TensorList bins, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_from_bin_tensors_out::call(self, bins, weight, density, out); +} +// aten::_histogramdd_from_bin_tensors.out(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _histogramdd_from_bin_tensors_outf(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, at::Tensor & out) { + return at::_ops::_histogramdd_from_bin_tensors_out::call(self, bins, weight, density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44b66a2d7bb97c4f50e6e8cc33751232240c77a3 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_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 & _histogramdd_from_bin_tensors_out(at::Tensor & out, const at::Tensor & self, at::TensorList bins, const ::std::optional & weight={}, bool density=false); +TORCH_API at::Tensor & _histogramdd_from_bin_tensors_outf(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ec18f89f6174bfe202e7fad442c7e3f2fb5b9da9 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_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 _histogramdd_from_bin_tensors(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight={}, bool density=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ceb97d09aac7568e8ea709f87628700d00041264 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_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_tensors_out(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, at::Tensor & out); +TORCH_API at::Tensor _histogramdd(const at::Tensor & self, at::TensorList bins, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8010026d1c3ca0ba546f33fbb6f78f1e2559eccc --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_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 _histogramdd_from_bin_tensors { + using schema = at::Tensor (const at::Tensor &, at::TensorList, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_from_bin_tensors"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_histogramdd_from_bin_tensors(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density); +}; + +struct TORCH_API _histogramdd_from_bin_tensors_out { + using schema = at::Tensor & (const at::Tensor &, at::TensorList, const ::std::optional &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_from_bin_tensors"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_histogramdd_from_bin_tensors.out(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl.h new file mode 100644 index 0000000000000000000000000000000000000000..817d94a7c8888141bb174579e496df666f47edba --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl.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::_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!) +inline at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false) { + return at::_ops::_index_put_impl_::call(self, indices, values, accumulate, unsafe); +} + +// aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::_index_put_impl_out::call(self, indices, values, accumulate, unsafe, out); +} +// aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::_index_put_impl_out::call(self, indices, values, accumulate, unsafe, out); +} + +// aten::_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor +inline 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) { + return at::_ops::_index_put_impl::call(self, indices, values, accumulate, unsafe); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3c43dafd20205031389d9ef3ba757490d5acfc57 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d650d1a8e564a66d0b001604676c185bd742fa9f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_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 & _index_put_impl_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ddfbdf06414d0cc7133b58ddf1096dbf6f6f3a8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_meta_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..57f52265eb554b090f67af0e7a86be3a4974bf55 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_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 & _index_put_impl_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); + +} // 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_native.h new file mode 100644 index 0000000000000000000000000000000000000000..971ff3234b07152888d5a378fa3c466b0ad1b3a5 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b67ccd40d5c02591fd3ad51f9282b559d69c8343 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _index_put_impl_ { + using schema = at::Tensor & (at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_index_put_impl_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); +}; + +struct TORCH_API _index_put_impl_out { + using schema = at::Tensor & (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_index_put_impl"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out); +}; + +struct TORCH_API _index_put_impl { + using schema = at::Tensor (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_index_put_impl"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices.h new file mode 100644 index 0000000000000000000000000000000000000000..7d7967b17ae776747398df2f9a35f1a504736a6a --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..71d4b0747440df5c4297c9b3d98cdd5f981f2d23 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_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::_indices_copy(Tensor self) -> Tensor +inline at::Tensor _indices_copy(const at::Tensor & self) { + return at::_ops::_indices_copy::call(self); +} + +// aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _indices_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_indices_copy_out::call(self, out); +} +// aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _indices_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_indices_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9e024dffaa4ad02e0aae6dd8c542e60d8589533 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a40b70c4a5b6ec7d5ffabdefc29f9202ae4401a7 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_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 _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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d5005c6e00b76f6eb410c618dcf36944cfc45ab2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_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 & _indices_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _indices_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..33d93f1fd2de65e92b5129f8f2e7373399ab0072 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _indices_copy { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_indices_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_indices_copy(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _indices_copy_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_indices_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f23b7e36652a66851b1f51410c36d711bc5013e8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_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 at::Tensor _indices_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1d6e2f15aa6158f8e7a04b32aa42d6ba3dea904f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_indices_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _indices { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_indices(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..6884a3515ee64cf41e0a86f61e10df09c3ef0b09 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm.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::_int_mm(Tensor self, Tensor mat2) -> Tensor +inline at::Tensor _int_mm(const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::_int_mm::call(self, mat2); +} + +// aten::_int_mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _int_mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::_int_mm_out::call(self, mat2, out); +} +// aten::_int_mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _int_mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::_int_mm_out::call(self, mat2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_cpu_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8b1a912d596ad94b9f0e203556c6e8253afbcd8f --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_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 _int_mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_cuda_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d5d6feb1316b45debc89be2bc16c025b1e285714 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_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 _int_mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_outf(const at::Tensor & self, const at::Tensor & mat2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..66dd22fe218e5d4ca448978bd637520b13251e75 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_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 _int_mm_cpu(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_out_cpu(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _int_mm_cuda(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _int_mm_out_cuda(const at::Tensor & self, const at::Tensor & mat2, 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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..96e0e81efc0d4655bbdb625ae01554d53b01b14d --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_int_mm_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 _int_mm { + 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::_int_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_int_mm(Tensor self, Tensor mat2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2); +}; + +struct TORCH_API _int_mm_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::_int_mm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_int_mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true.h new file mode 100644 index 0000000000000000000000000000000000000000..f164af4080144d4eee050e1eb338c79d6b90a3ca --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true.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_all_true(Tensor self) -> Tensor +inline at::Tensor _is_all_true(const at::Tensor & self) { + return at::_ops::_is_all_true::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79c6731b8500566a8749da7e0a6d787bd4eac693 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_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_all_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_native.h new file mode 100644 index 0000000000000000000000000000000000000000..399b838cea5b5e6449b798042a41462b375f01a8 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..165fbaf0538a42c213fdfa241602455629c01c53 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_all_true_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_all_true { + 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::_is_all_true"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_is_all_true(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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true.h new file mode 100644 index 0000000000000000000000000000000000000000..5f8f32ea0fc043b002ab2295e073010f1611cff2 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true.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_any_true(Tensor self) -> Tensor +inline at::Tensor _is_any_true(const at::Tensor & self) { + return at::_ops::_is_any_true::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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_compositeexplicitautograd_dispatch.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ec11d1e8f320dcbffc71f4cfbf1213614773e36 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_native.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3f970116420699adb1c87228ac513c1e23f15719 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_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_any_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/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_ops.h b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e4ab25ecf8dc5a0996401d0ca5700f2e265f8487 --- /dev/null +++ b/miniconda3/envs/active_proaction/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true_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_any_true { + 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::_is_any_true"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_is_any_true(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)