diff --git a/.gitattributes b/.gitattributes index 40f4b2f665e7e3df95b4cb4e537e0feda6e9de95..80cd5c7e3731c424e0f920c548c28cb21f958d61 100644 --- a/.gitattributes +++ b/.gitattributes @@ -146,3 +146,4 @@ tuning-competition-baseline/.venv/lib/python3.11/site-packages/torch/_inductor/_ .venv/lib/python3.11/site-packages/torch/_inductor/codegen/__pycache__/cpp.cpython-311.pyc filter=lfs diff=lfs merge=lfs -text .venv/lib/python3.11/site-packages/torch/_inductor/codegen/__pycache__/common.cpython-311.pyc filter=lfs diff=lfs merge=lfs -text .venv/lib/python3.11/site-packages/torch/_inductor/fx_passes/__pycache__/split_cat.cpython-311.pyc filter=lfs diff=lfs merge=lfs -text +.venv/lib/python3.11/site-packages/nvidia/cudnn/lib/libcudnn_adv.so.9 filter=lfs diff=lfs merge=lfs -text diff --git a/.venv/lib/python3.11/site-packages/nvidia/cudnn/lib/libcudnn_adv.so.9 b/.venv/lib/python3.11/site-packages/nvidia/cudnn/lib/libcudnn_adv.so.9 new file mode 100644 index 0000000000000000000000000000000000000000..257de8f5d329fc74577805ba58d1858a4984a587 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/nvidia/cudnn/lib/libcudnn_adv.so.9 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:be8174726a8d152bcf6e136b2d1f81763876deb1d2b7329bbc7d2a52635b0202 +size 240706416 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Byte_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Byte_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..641a371ea186c40cf734240bcbf12c598d562c45 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Byte_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cast_Byte { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cast_Byte") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Long_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Long_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c5911881eda6b4213dcf7fe0c426188c3b4c1e6c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Long_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _cast_Long(const at::Tensor & self, bool non_blocking=false); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cholesky_solve_helper.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cholesky_solve_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..014971c6f8e9d8ad3b80c6317d5830864d6b8d86 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cholesky_solve_helper.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cholesky_solve_helper(Tensor self, Tensor A, bool upper) -> Tensor +inline at::Tensor _cholesky_solve_helper(const at::Tensor & self, const at::Tensor & A, bool upper) { + return at::_ops::_cholesky_solve_helper::call(self, A, upper); +} + +// aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cholesky_solve_helper_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & A, bool upper) { + return at::_ops::_cholesky_solve_helper_out::call(self, A, upper, out); +} +// aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cholesky_solve_helper_outf(const at::Tensor & self, const at::Tensor & A, bool upper, at::Tensor & out) { + return at::_ops::_cholesky_solve_helper_out::call(self, A, upper, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f16336dc11433747431aa75334eb7605690ca20e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_debug_has_internal_overlap_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..88807c54b27b6510b6e12e04b951b8f8f91787c1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag_forward_only") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag_forward_only") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_acos_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_acos_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3df8eb38caae007b55c38fa214fe8fb426ac5c7f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_acos_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it 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 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..afd15a7ddf3b1adbcf8427e67cf7547328cd0add --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_floor_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..946bec271173fa5f4d2f0150300ac2ea24823d90 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_reciprocal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_reciprocal_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_reciprocal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_sdp_choice_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_sdp_choice_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7965df783b130ec8730fd77d2a531b99bb013f8e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_sdp_choice_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_sdp_choice") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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 diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_values_copy_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_values_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3a26faef612701e977c2d92eb4ce39a0977cb28a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_values_copy_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _nested_get_values_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _nested_get_values_copy(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_alias_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_alias_native.h new file mode 100644 index 0000000000000000000000000000000000000000..64e465c6a52399e614c45c07046a56d6ab3c7d03 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_alias_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _reshape_alias(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_mm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..ba192b617eb6a7fae58c684f5286659147ff87ec --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_mm.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_scaled_mm(Tensor self, Tensor mat2, Tensor scale_a, Tensor scale_b, Tensor? bias=None, Tensor? scale_result=None, ScalarType? out_dtype=None, bool use_fast_accum=False) -> Tensor +inline at::Tensor _scaled_mm(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias={}, const ::std::optional & scale_result={}, ::std::optional out_dtype=::std::nullopt, bool use_fast_accum=false) { + return at::_ops::_scaled_mm::call(self, mat2, scale_a, scale_b, bias, scale_result, out_dtype, use_fast_accum); +} + +// aten::_scaled_mm.out(Tensor self, Tensor mat2, Tensor scale_a, Tensor scale_b, Tensor? bias=None, Tensor? scale_result=None, ScalarType? out_dtype=None, bool use_fast_accum=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _scaled_mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias={}, const ::std::optional & scale_result={}, ::std::optional out_dtype=::std::nullopt, bool use_fast_accum=false) { + return at::_ops::_scaled_mm_out::call(self, mat2, scale_a, scale_b, bias, scale_result, out_dtype, use_fast_accum, out); +} +// aten::_scaled_mm.out(Tensor self, Tensor mat2, Tensor scale_a, Tensor scale_b, Tensor? bias=None, Tensor? scale_result=None, ScalarType? out_dtype=None, bool use_fast_accum=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _scaled_mm_outf(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias, const ::std::optional & scale_result, ::std::optional out_dtype, bool use_fast_accum, at::Tensor & out) { + return at::_ops::_scaled_mm_out::call(self, mat2, scale_a, scale_b, bias, scale_result, out_dtype, use_fast_accum, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_segment_reduce_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_segment_reduce_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..43cc72d84ce83500c4b51f346c962191a8212ec6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_segment_reduce_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _segment_reduce_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const ::std::optional &, const ::std::optional &, int64_t, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_segment_reduce_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_segment_reduce_backward(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None) -> Tensor") + static at::Tensor call(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths, const ::std::optional & offsets, int64_t axis, const ::std::optional & initial); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths, const ::std::optional & offsets, int64_t axis, const ::std::optional & initial); +}; + +struct TORCH_API _segment_reduce_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const ::std::optional &, const ::std::optional &, int64_t, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_segment_reduce_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths, const ::std::optional & offsets, int64_t axis, const ::std::optional & initial, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths, const ::std::optional & offsets, int64_t axis, const ::std::optional & initial, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..156e618d581416743636150a9d44c665f20ccaea --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _softmax(const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ae31fb6eaa602ef24d8c72d3acda97df0e4cd6fe --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _sparse_semi_structured_apply_dense(const at::Tensor & input, const at::Tensor & thread_masks); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b630be4f67486da6f8affa8ea6a893ddf751f80a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_semi_structured_mm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_semi_structured_mm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_semi_structured_mm(Tensor mat1, Tensor mat1_meta, Tensor mat2, *, ScalarType? out_dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, ::std::optional out_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, ::std::optional out_dtype); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..acdcf8ce8787b4d24a93bd56fcc0013b7ecf0af0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _sparse_semi_structured_tile(const at::Tensor & input, c10::string_view algorithm="", bool use_cutlass=true); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..03c5bac237c09c57bbd870d99a3222a631fc827e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _sparse_softmax_backward_data_out(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor softmax_backward_sparse_cpu(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +TORCH_API at::Tensor softmax_backward_sparse_cuda(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_csc_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_csc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1468d03e0ca884293018672cb95c049332a13971 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_csc_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 & _to_sparse_csc_out(at::Tensor & out, const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor & _to_sparse_csc_outf(const at::Tensor & self, ::std::optional dense_dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3202a90a5e06795b6119524d184e59ff3b3e0869 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _transformer_encoder_layer_fwd_out(at::Tensor & out, const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask={}, ::std::optional mask_type=::std::nullopt); +TORCH_API at::Tensor & _transformer_encoder_layer_fwd_outf(const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask, ::std::optional mask_type, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_values_copy_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_values_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5fba88bfa4ef1f9c5d2851ac91b4306acab0396c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_values_copy_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _values_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _values_copy(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bincount_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bincount_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..785e9ec21ccec6c64c534cc36ffb55ac61b3c346 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bincount_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bincount { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bincount") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor") + static at::Tensor call(const at::Tensor & self, const ::std::optional & weights, int64_t minlength); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & weights, int64_t minlength); +}; + +struct TORCH_API bincount_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bincount") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const ::std::optional & weights, int64_t minlength, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & weights, int64_t minlength, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cat_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cat_native.h new file mode 100644 index 0000000000000000000000000000000000000000..36f6c7f8c89009bb4e201b045263d8ebde3776fb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cat_native.h @@ -0,0 +1,32 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_cat_out_cpu : public at::meta::structured_cat { +void impl(const at::ITensorListRef & tensors, int64_t dim, int64_t valid, bool all_contiguous, bool all_same_dtype, bool all_same_sizes_and_stride, at::MemoryFormat memory_format, const at::Tensor & out); +}; +struct TORCH_API structured_cat_out_cuda : public at::meta::structured_cat { +void impl(const at::ITensorListRef & tensors, int64_t dim, int64_t valid, bool all_contiguous, bool all_same_dtype, bool all_same_sizes_and_stride, at::MemoryFormat memory_format, const at::Tensor & out); +}; +TORCH_API at::Tensor cat_nested(const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor cat_sparse(const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor cat_quantized_cpu(const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor & cat_out_quantized_cpu(const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out); +TORCH_API at::Tensor cat(at::TensorList tensors, at::Dimname dim); +TORCH_API at::Tensor & cat_out(at::TensorList tensors, at::Dimname dim, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cauchy_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cauchy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c9c01e9e5cf7fdc6800d224dd4f87bb4aa55cfb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cauchy_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cauchy_ { + using schema = at::Tensor & (at::Tensor &, double, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cauchy_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cauchy_(Tensor(a!) self, float median=0, float sigma=1, *, Generator? generator=None) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, double median, double sigma, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double median, double sigma, ::std::optional generator); +}; + +struct TORCH_API cauchy_out { + using schema = at::Tensor & (const at::Tensor &, double, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cauchy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cauchy.out(Tensor self, float median=0, float sigma=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, double median, double sigma, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double median, double sigma, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API cauchy { + using schema = at::Tensor (const at::Tensor &, double, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cauchy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cauchy(Tensor self, float median=0, float sigma=1, *, Generator? generator=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, double median, double sigma, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double median, double sigma, ::std::optional generator); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ccol_indices_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ccol_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9488be886889b817bcb942abd86f758553b0eba8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ccol_indices_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor ccol_indices_default(const at::Tensor & self); +TORCH_API at::Tensor ccol_indices_sparse_csr(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky.h new file mode 100644 index 0000000000000000000000000000000000000000..014812ded08d582bdcca4e22d0c058cc6f655d4b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cholesky_out(at::Tensor & out, const at::Tensor & self, bool upper=false) { + return at::_ops::cholesky_out::call(self, upper, out); +} +// aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cholesky_outf(const at::Tensor & self, bool upper, at::Tensor & out) { + return at::_ops::cholesky_out::call(self, upper, out); +} + +// aten::cholesky(Tensor self, bool upper=False) -> Tensor +inline at::Tensor cholesky(const at::Tensor & self, bool upper=false) { + return at::_ops::cholesky::call(self, upper); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ba83f29fd591e4f629cfdd6fb2d4a0094f9c1609 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cudnn_batch_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cudnn_batch_norm_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace); +}; + +struct TORCH_API cudnn_batch_norm_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cudnn_batch_norm_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cudnn_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_strided.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_strided.h new file mode 100644 index 0000000000000000000000000000000000000000..bd757c0774ec6649f85b48d57ab200f9858d8dde --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_strided.h @@ -0,0 +1,113 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}) { + return at::_ops::empty_strided::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}) { + return at::_ops::empty_strided::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::empty_strided::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::empty_strided::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), dtype, layout, device, pin_memory); + } +} + +// aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={}) { + return at::_ops::empty_strided::call(size, stride, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor empty_strided(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={}) { + return at::_ops::empty_strided::call(size, stride, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::empty_strided::call(size, stride, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor empty_strided(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::empty_strided::call(size, stride, dtype, layout, device, pin_memory); + } +} + +// aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & empty_strided_out(at::Tensor & out, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::empty_strided_out::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & empty_strided_out(at::Tensor & out, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::empty_strided_out::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & empty_strided_outf(at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::empty_strided_out::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & empty_strided_outf(at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::empty_strided_out::call(c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & empty_strided_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::empty_strided_out::call(size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & empty_strided_out(at::Tensor & out, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::empty_strided_out::call(size, stride, out); + } +} + +// aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & empty_strided_symint_outf(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::empty_strided_out::call(size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & empty_strided_outf(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::empty_strided_out::call(size, stride, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_hfftn.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_hfftn.h new file mode 100644 index 0000000000000000000000000000000000000000..f587899f3232a05ea10bb7f8a410e82a9382a342 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_hfftn.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_hfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_hfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_hfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn::call(self, s, dim, norm); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfftn_symint_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_hfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfftn_out::call(self, s, dim, norm, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/flatten_dense_tensors_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/flatten_dense_tensors_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d80820903456f754bc3eea590f72e128a2521a96 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/flatten_dense_tensors_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @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 flatten_dense_tensors(at::TensorList tensors); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gather_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gather_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..807f2f4049014d4f7474a616a00d4cb6758981a6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gather_backward.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::gather_backward(Tensor grad, Tensor self, int dim, Tensor index, bool sparse_grad) -> Tensor +inline at::Tensor gather_backward(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad) { + return at::_ops::gather_backward::call(grad, self, dim, index, sparse_grad); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/glu_jvp_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/glu_jvp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca9787cfdd0220309bfbe2d4ea679a6803440a94 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/glu_jvp_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it 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 glu_jvp(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hamming_window_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hamming_window_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f1e715d831208133c25f8860a1541f289287ad62 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hamming_window_compositeexplicitautograd_dispatch.h @@ -0,0 +1,38 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 hamming_window(int64_t window_length, at::TensorOptions options={}); +TORCH_API at::Tensor hamming_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length); +TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, at::TensorOptions options={}); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic); +TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, at::TensorOptions options={}); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha); +TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, at::TensorOptions options={}); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha, double beta); +TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/huber_loss.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/huber_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..7cbb6920b29e526134270a4d1879decdb7bc45c3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/huber_loss.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::huber_loss.out(Tensor self, Tensor target, int reduction=Mean, float delta=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & huber_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0) { + return at::_ops::huber_loss_out::call(self, target, reduction, delta, out); +} +// aten::huber_loss.out(Tensor self, Tensor target, int reduction=Mean, float delta=1.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & huber_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out) { + return at::_ops::huber_loss_out::call(self, target, reduction, delta, out); +} + +// aten::huber_loss(Tensor self, Tensor target, int reduction=Mean, float delta=1.0) -> Tensor +inline at::Tensor huber_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0) { + return at::_ops::huber_loss::call(self, target, reduction, delta); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/igamma_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/igamma_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cdde4a83837aa257e9aa0628ca765d2aef550376 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/igamma_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_igamma : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf.h new file mode 100644 index 0000000000000000000000000000000000000000..37c65dfa52e9daa99a88fb796fdfa2b5737f005c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::isneginf(Tensor self) -> Tensor +inline at::Tensor isneginf(const at::Tensor & self) { + return at::_ops::isneginf::call(self); +} + +// aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::isneginf_out::call(self, out); +} +// aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::isneginf_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ee95465e0ff7d2100d0c4ee50262e48127785e7c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 isneginf(const at::Tensor & self); +TORCH_API at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isposinf_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isposinf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..203c4698bcf5bd9052d114ca2e25d44e4a2f06b2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isposinf_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_isposinf_out : public at::meta::structured_isposinf { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor isposinf_sparse(const at::Tensor & self); +TORCH_API at::Tensor & isposinf_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor isposinf_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & isposinf_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/leaky_relu_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/leaky_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3fbc282ab518dc9d8348d5042c79e3a6ad580cad --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/leaky_relu_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor leaky_relu(const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_outf(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out); +TORCH_API at::Tensor & leaky_relu_(at::Tensor & self, const at::Scalar & negative_slope=0.01); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/less_equal_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/less_equal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..74e1a74747a23599d524de477ea2d2b45e7d5b86 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/less_equal_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API less_equal_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::less_equal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API less_equal_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::less_equal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "less_equal.Scalar(Tensor self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API less_equal_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::less_equal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API less_equal_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::less_equal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "less_equal.Tensor(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API less_equal__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::less_equal_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "less_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API less_equal__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::less_equal_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "less_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linspace_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linspace_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cfaf717deb745b3b62bc8f2f8b88f32857b54cef --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linspace_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 & linspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps); +TORCH_API at::Tensor & linspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices.h new file mode 100644 index 0000000000000000000000000000000000000000..2371ed208b0e9866384a8bfc1bc01f1b0b73c37c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple max_pool2d_with_indices_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::max_pool2d_with_indices_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); +} +// aten::max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple max_pool2d_with_indices_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices) { + return at::_ops::max_pool2d_with_indices_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); +} + +// aten::max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) +inline ::std::tuple max_pool2d_with_indices(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::max_pool2d_with_indices::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d80928e8e32b3eb7dfe4b478502a54371cc55b3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 max_pool2d_with_indices_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); +TORCH_API at::Tensor & max_pool2d_with_indices_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); +TORCH_API at::Tensor & max_pool2d_with_indices_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d90d548483a1c96a86ab8b3e056f14f741a0fde9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API max_pool3d_with_indices_out { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::max_pool3d_with_indices") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); +}; + +struct TORCH_API max_pool3d_with_indices { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::max_pool3d_with_indices") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_unpool3d_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_unpool3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..24efbc157c4a474569e90b9c1241265e267d5efd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_unpool3d_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 max_unpool3d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor max_unpool3d_symint(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpool3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpool3d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & max_unpool3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpool3d_symint_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a1399eaa5575a1a830d7a1d493a03595302cb697 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mkldnn_reorder_conv2d_weight { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_reorder_conv2d_weight") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_reorder_conv2d_weight(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); +}; + +struct TORCH_API mkldnn_reorder_conv2d_weight_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_reorder_conv2d_weight") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_reorder_conv2d_weight.out(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bde301cc371ac8c109799990542656f18b6b3d98 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multiply_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multiply_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a7c3737e20c0daba70dd8f2375d55205c6bd7275 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multiply_ops.h @@ -0,0 +1,72 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API multiply_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multiply") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multiply.Tensor(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API multiply__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multiply_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multiply_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API multiply_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multiply") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API multiply_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multiply") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multiply.Scalar(Tensor self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API multiply__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multiply_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multiply_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mvlgamma_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mvlgamma_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be28c123efab9206c637ea22095cb6a9a22a2842 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mvlgamma_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it 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 & mvlgamma_out(at::Tensor & out, const at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_outf(const at::Tensor & self, int64_t p, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_norm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..6792c3426973f398c9087deb311cb5028e98ce7c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_norm.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_norm(Tensor self, Scalar p=2) -> Tensor +inline at::Tensor native_norm(const at::Tensor & self, const at::Scalar & p=2) { + return at::_ops::native_norm::call(self, p); +} + +// aten::native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor +inline at::Tensor native_norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype) { + return at::_ops::native_norm_ScalarOpt_dim_dtype::call(self, p, dim, keepdim, dtype); +} + +// aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & p=2) { + return at::_ops::native_norm_out::call(self, p, out); +} +// aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_outf(const at::Tensor & self, const at::Scalar & p, at::Tensor & out) { + return at::_ops::native_norm_out::call(self, p, out); +} + +// aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype) { + return at::_ops::native_norm_ScalarOpt_dim_dtype_out::call(self, p, dim, keepdim, dtype, out); +} +// aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & native_norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::native_norm_ScalarOpt_dim_dtype_out::call(self, p, dim, keepdim, dtype, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nll_loss_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nll_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..823683ccf9d99c46cf760faa9998ca6c218d1dc6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nll_loss_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor +inline at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); +} +namespace symint { + template ::value>> + at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); + } +} + +// aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor +inline at::Tensor nll_loss_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); +} +namespace symint { + template ::value>> + at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nuclear_norm_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nuclear_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ef594d0dbbe0ce77d09390f9ebc5a173a1c8f87f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nuclear_norm_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nuclear_norm { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nuclear_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nuclear_norm(Tensor self, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool keepdim); +}; + +struct TORCH_API nuclear_norm_out { + using schema = at::Tensor & (const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nuclear_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API nuclear_norm_dim { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nuclear_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nuclear_norm.dim(Tensor self, int[2] dim, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim); +}; + +struct TORCH_API nuclear_norm_dim_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nuclear_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nuclear_norm.dim_out(Tensor self, int[2] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/promote_types_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/promote_types_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a499c5e891e9b4da722a4a75047b11846bbac773 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/promote_types_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API promote_types { + using schema = at::ScalarType (at::ScalarType, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::promote_types") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "promote_types(ScalarType type1, ScalarType type2) -> ScalarType") + static at::ScalarType call(at::ScalarType type1, at::ScalarType type2); + static at::ScalarType redispatch(c10::DispatchKeySet dispatchKeySet, at::ScalarType type1, at::ScalarType type2); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/put.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/put.h new file mode 100644 index 0000000000000000000000000000000000000000..d0d095f742421dc8b252ec932349d81d9ace8214 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/put.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::put(Tensor self, Tensor index, Tensor source, bool accumulate=False) -> Tensor +inline at::Tensor put(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false) { + return at::_ops::put::call(self, index, source, accumulate); +} + +// aten::put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & put_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false) { + return at::_ops::put_out::call(self, index, source, accumulate, out); +} +// aten::put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & put_outf(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out) { + return at::_ops::put_out::call(self, index, source, accumulate, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0d7f3d129411618c070e05c4b1ec5b949911eb91 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randint_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randint_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e07d44afdb9faf66871d14a975e8d17b7b1bc0fa --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randint_native.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ravel_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ravel_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..32399bd67141f716b05d26dfa46e036f35c00bc2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ravel_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API ravel { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::ravel") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "ravel(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/refine_names_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/refine_names_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6de924f2068befcfc9115189dfc0de17beb1c95b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/refine_names_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor refine_names(const at::Tensor & self, at::DimnameList names); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rnn_relu.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rnn_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..4ae0cf6bc042799148e0c8fd645f44cc6923c99f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rnn_relu.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::rnn_relu.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor) +inline ::std::tuple rnn_relu(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) { + return at::_ops::rnn_relu_input::call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); +} + +// aten::rnn_relu.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor) +inline ::std::tuple rnn_relu(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) { + return at::_ops::rnn_relu_data::call(data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/row_indices_copy_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/row_indices_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..09f97ce215ac582e2c914ae9bf85f5752190d7dd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/row_indices_copy_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & row_indices_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor row_indices_copy(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsub_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f901c4ab46aaf01cd2db626c1f645bcd54247b6a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsub_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API rsub_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rsub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rsub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API rsub_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rsub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rsub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API rsub_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rsub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rsub.Tensor_out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +}; + +struct TORCH_API rsub_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rsub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rsub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/set_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/set_native.h new file mode 100644 index 0000000000000000000000000000000000000000..356b87092ff8ec9b3121bf3a2b900cf7c7572408 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/set_native.h @@ -0,0 +1,38 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor set(const at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_source_Storage_out(const at::Tensor & self, at::Storage source, at::Tensor & out); +TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source); +TORCH_API at::Tensor set_symint(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_source_Storage_storage_offset_out_symint(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor & set_storage_cpu_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set_storage_cuda_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set_storage_meta__symint(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_storage_quantized_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set__symint(at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor set(const at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_source_Tensor_out(const at::Tensor & self, const at::Tensor & source, at::Tensor & out); +TORCH_API at::Tensor & set_tensor_(at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor set(const at::Tensor & self); +TORCH_API at::Tensor & set_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & set_cpu_(at::Tensor & self); +TORCH_API at::Tensor & set_cuda_(at::Tensor & self); +TORCH_API at::Tensor & set_meta_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sin_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sin_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2ffca294221ef2c712e4d57eb1cbc9582946c748 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sin_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 sin(const at::Tensor & self); +TORCH_API at::Tensor & sin_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sin_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sin_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinh_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d6f6c423497449d155ae3af0e75439e4a6e65e8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinh_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it 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 sinh(const at::Tensor & self); +TORCH_API at::Tensor & sinh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80888db87f6cb19c752e3ca9be501c9354f1a7d1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv_transpose3d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API slow_conv_transpose3d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slow_conv_transpose3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slow_conv_transpose3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, SymInt[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out); +}; + +struct TORCH_API slow_conv_transpose3d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slow_conv_transpose3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slow_conv_transpose3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, SymInt[3] dilation=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softplus_backward_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softplus_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..abfef0970f37f9baa3e37f002a89695377dfdfbc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softplus_backward_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_softplus_backward : public TensorIteratorBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u.h new file mode 100644 index 0000000000000000000000000000000000000000..e0a76bc6fc2a92dab9152dc73eaf55dade4cdb4c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_u(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_u::call(x, n); +} + +// aten::special_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_u(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_u_x_scalar::call(x, n); +} + +// aten::special_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_u(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_chebyshev_polynomial_u_n_scalar::call(x, n); +} + +// aten::special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_u_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_u_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_u_out::call(x, n, out); +} + +// aten::special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_u_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_u_x_scalar_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_u_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_u_x_scalar_out::call(x, n, out); +} + +// aten::special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_chebyshev_polynomial_u_n_scalar_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_u_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_u_n_scalar_out::call(x, n, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e90ea164a1ca94cd75aac0caef7281bd3bc54958 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_hermite_polynomial_he(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_hermite_polynomial_he(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff00aaa2c54ea729e7115e4febd79b130801ac2a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it 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 sqrt(const at::Tensor & self); +TORCH_API at::Tensor & sqrt_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sqrt_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sqrt_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ead92c4e782fa43da8357e777b7fea6dda547a24 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 std(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f28095cff8865335712fdbfcdd4c06dfc57e5543 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 swapdims(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor & swapdims_(at::Tensor & self, int64_t dim0, int64_t dim1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/t_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/t_native.h new file mode 100644 index 0000000000000000000000000000000000000000..94c9acbe526ef0c48e83f69bd62a44600d9c8f0b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/t_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @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 t(const at::Tensor & self); +TORCH_API at::Tensor & t_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take_along_dim.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take_along_dim.h new file mode 100644 index 0000000000000000000000000000000000000000..1d1437349dfb4f16bfde9db4578dc13ccd363d9a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take_along_dim.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_along_dim_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim=::std::nullopt) { + return at::_ops::take_along_dim_out::call(self, indices, dim, out); +} +// aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_along_dim_outf(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out) { + return at::_ops::take_along_dim_out::call(self, indices, dim, out); +} + +// aten::take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor +inline at::Tensor take_along_dim(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim=::std::nullopt) { + return at::_ops::take_along_dim::call(self, indices, dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..68e3727e44bb341665c6218bdab80302b2a2a6e7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor take(const at::Tensor & self, const at::Tensor & index); +TORCH_API at::Tensor & take_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index); +TORCH_API at::Tensor & take_outf(const at::Tensor & self, const at::Tensor & index, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b6940f845cd2ba9d0300001907e23ab542bf56d3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); + +} // namespace cpu +} // namespace at