diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convolution_double_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convolution_double_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..895db8094d9febfddffd9ea45b2415900e8467d2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convolution_double_backward.h @@ -0,0 +1,47 @@ +#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::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _convolution_double_backward(const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::_convolution_double_backward::call(ggI, ggW, ggb, gO, weight, self, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask); +} +namespace symint { + template ::value>> + ::std::tuple _convolution_double_backward(const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::_convolution_double_backward::call(ggI, ggW, ggb, gO, weight, self, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask); + } +} + +// aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _convolution_double_backward_symint(const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::_convolution_double_backward::call(ggI, ggW, ggb, gO, weight, self, stride, padding, dilation, transposed, output_padding, groups, output_mask); +} +namespace symint { + template ::value>> + ::std::tuple _convolution_double_backward(const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::_convolution_double_backward::call(ggI, ggW, ggb, gO, weight, self, stride, padding, dilation, transposed, output_padding, groups, output_mask); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a5cd2aff65e7acbd45dae7c7e5e6e291493d17ce --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_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 { + 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") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx); +}; + +struct TORCH_API _embedding_bag_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool, int64_t, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..044d98cbec3c38c42e7b0f6399f8e21d1bc7eba9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _fake_quantize_learnable_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fft_c2c.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fft_c2c.h new file mode 100644 index 0000000000000000000000000000000000000000..cf0c26b7be3d2e6cea46a7d48f3ad6f60468c43b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fft_c2c.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_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor +inline at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward); + } +} + +// aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor +inline at::Tensor _fft_c2c_symint(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, dim, normalization, forward); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2c(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c::call(self, dim, normalization, forward); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, c10::fromIntArrayRefSlow(dim), normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); + } +} + +// aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2c_symint_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2c_outf(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out) { + return at::_ops::_fft_c2c_out::call(self, dim, normalization, forward, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5cf8e7b30c965bd6e40b95cde9afd66e48f3334f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10_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_log10(at::TensorList self); +TORCH_API void _foreach_log10_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_log10_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_log10_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_functional_assert_async.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_functional_assert_async.h new file mode 100644 index 0000000000000000000000000000000000000000..21ed89c364e2d0c2f4d09d082e93b8139962c832 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_functional_assert_async.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::_functional_assert_async.msg(Tensor self, str assert_msg, Tensor dep_token) -> Tensor +inline at::Tensor _functional_assert_async(const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token) { + return at::_ops::_functional_assert_async_msg::call(self, assert_msg, dep_token); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_lazy_clone_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_lazy_clone_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..14155c8bdbb936089ed9586e3e0522c391aa7742 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_lazy_clone_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 _lazy_clone { + 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::_lazy_clone") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_lazy_clone(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_masked_softmax.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_masked_softmax.h new file mode 100644 index 0000000000000000000000000000000000000000..ff3e9c894809afad084447f91f5a97079a3918a0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_masked_softmax.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::_masked_softmax(Tensor self, Tensor mask, int? dim=None, int? mask_type=None) -> Tensor +inline at::Tensor _masked_softmax(const at::Tensor & self, const at::Tensor & mask, ::std::optional dim=::std::nullopt, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_masked_softmax::call(self, mask, dim, mask_type); +} + +// aten::_masked_softmax.out(Tensor self, Tensor mask, int? dim=None, int? mask_type=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _masked_softmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, ::std::optional dim=::std::nullopt, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_masked_softmax_out::call(self, mask, dim, mask_type, out); +} +// aten::_masked_softmax.out(Tensor self, Tensor mask, int? dim=None, int? mask_type=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _masked_softmax_outf(const at::Tensor & self, const at::Tensor & mask, ::std::optional dim, ::std::optional mask_type, at::Tensor & out) { + return at::_ops::_masked_softmax_out::call(self, mask, dim, mask_type, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d13f044793a1c3a3c5c4e8d5b2c9898e424f712d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_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 bool NestedTensor_nested_tensor_from_mask_left_aligned(const at::Tensor & t, const at::Tensor & mask); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..211b9fe4ebf60200af1b28578de77e8015c672c4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_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 _nested_view_from_buffer { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_nested_view_from_buffer") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_view_from_buffer(Tensor(a) self, Tensor nested_size, Tensor nested_strides, Tensor offsets) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_new_zeros_with_same_feature_meta_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_new_zeros_with_same_feature_meta_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b54d055631ae64d33e7c17b0fc9efa043c7ec26c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_new_zeros_with_same_feature_meta_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 _new_zeros_with_same_feature_meta(const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims=0); +TORCH_API at::Tensor & _new_zeros_with_same_feature_meta_out(const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..bde5afca303fae26e83e81ce7c2767951b693cb1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution.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::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1) -> Tensor +inline at::Tensor _nnpack_spatial_convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride=1) { + return at::_ops::_nnpack_spatial_convolution::call(input, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride)); +} +namespace symint { + template ::value>> + at::Tensor _nnpack_spatial_convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride=1) { + return at::_ops::_nnpack_spatial_convolution::call(input, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride)); + } +} + +// aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1) -> Tensor +inline at::Tensor _nnpack_spatial_convolution_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride=c10::SymInt(1)) { + return at::_ops::_nnpack_spatial_convolution::call(input, weight, bias, padding, stride); +} +namespace symint { + template ::value>> + at::Tensor _nnpack_spatial_convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride=c10::SymInt(1)) { + return at::_ops::_nnpack_spatial_convolution::call(input, weight, bias, padding, stride); + } +} + +// aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nnpack_spatial_convolution_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride=1) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & _nnpack_spatial_convolution_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride=1) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nnpack_spatial_convolution_outf(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & _nnpack_spatial_convolution_outf(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nnpack_spatial_convolution_symint_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride=c10::SymInt(1)) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, padding, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & _nnpack_spatial_convolution_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride=c10::SymInt(1)) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, padding, stride, out); + } +} + +// aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nnpack_spatial_convolution_symint_outf(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, padding, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & _nnpack_spatial_convolution_outf(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::_nnpack_spatial_convolution_out::call(input, weight, bias, padding, stride, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_pad_enum.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_pad_enum.h new file mode 100644 index 0000000000000000000000000000000000000000..24146aac3470fb29cc6a7600f3e40e33694d8e2c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_pad_enum.h @@ -0,0 +1,47 @@ +#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::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor +inline at::Tensor _pad_enum(const at::Tensor & self, at::IntArrayRef pad, int64_t mode, ::std::optional value=::std::nullopt) { + return at::_ops::_pad_enum::call(self, c10::fromIntArrayRefSlow(pad), mode, value); +} +namespace symint { + template ::value>> + at::Tensor _pad_enum(const at::Tensor & self, at::IntArrayRef pad, int64_t mode, ::std::optional value=::std::nullopt) { + return at::_ops::_pad_enum::call(self, c10::fromIntArrayRefSlow(pad), mode, value); + } +} + +// aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor +inline at::Tensor _pad_enum_symint(const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, ::std::optional value=::std::nullopt) { + return at::_ops::_pad_enum::call(self, pad, mode, value); +} +namespace symint { + template ::value>> + at::Tensor _pad_enum(const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, ::std::optional value=::std::nullopt) { + return at::_ops::_pad_enum::call(self, pad, mode, value); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_prelu_kernel_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_prelu_kernel_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d5c48829c5b9e271af872659253938357dcbb2b9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_prelu_kernel_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 _prelu_kernel { + 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::_prelu_kernel") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_prelu_kernel(Tensor self, Tensor weight) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4d13f60fa94538d837ef4b87508a6ce9573d78ed --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_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 at::Tensor & _to_sparse_out(at::Tensor & out, const at::Tensor & self, int64_t sparse_dim); +TORCH_API at::Tensor & _to_sparse_outf(const at::Tensor & self, int64_t sparse_dim, at::Tensor & out); +TORCH_API at::Tensor & _to_sparse_out(at::Tensor & out, const at::Tensor & self, ::std::optional layout=::std::nullopt, at::OptionalIntArrayRef blocksize=::std::nullopt, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor & _to_sparse_outf(const at::Tensor & self, ::std::optional layout, at::OptionalIntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..664850e909b60114870c227e26b46fca22b11de1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_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 ::std::tuple _unpack_dual(const at::Tensor & dual, int64_t level); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3f1af0abc5a4f70ea3dc04da71e70922a8c9ef47 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward_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 ::std::tuple _weight_norm_interface_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim); +TORCH_API ::std::tuple _weight_norm_interface_backward_outf(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acos.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acos.h new file mode 100644 index 0000000000000000000000000000000000000000..7b588057de0e166bcfa57f8ab14c086fcf122a20 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acos.h @@ -0,0 +1,44 @@ +#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::acos(Tensor self) -> Tensor +inline at::Tensor acos(const at::Tensor & self) { + return at::_ops::acos::call(self); +} + +// aten::acos_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & acos_(at::Tensor & self) { + return at::_ops::acos_::call(self); +} + +// aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & acos_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::acos_out::call(self, out); +} +// aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & acos_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::acos_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acosh_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acosh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..574217ea22005352e027d94a892dd6cf9eab649a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acosh_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 acosh { + 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::acosh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "acosh(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API acosh_ { + using schema = 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::acosh_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "acosh_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API acosh_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::acosh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "acosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/all_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/all_native.h new file mode 100644 index 0000000000000000000000000000000000000000..272b358c4860353ca736499bccbac12f00881470 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/all_native.h @@ -0,0 +1,34 @@ +#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_all_out : public at::meta::structured_all_dim { +void impl(const at::Tensor & self, int64_t dim, bool keepdim, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_all(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor all_dims_default(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & all_dims_out_default(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); +struct TORCH_API structured_all_dims_out : public at::meta::structured_all_dims { +void impl(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, const at::Tensor & out); +}; +TORCH_API at::Tensor all(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & all_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); +struct TORCH_API structured_all_all_out : public at::meta::structured_all { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan2_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan2_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8a2f5831e1a9510e71dc5b35072f722566219b2c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan2_cpu_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 cpu { + +TORCH_API at::Tensor atan2(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & atan2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & atan2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & atan2_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ce4a975bd0c467f2970965ec899df29ad17db3df --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_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 batch_norm { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::batch_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor") + static at::Tensor call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, bool cudnn_enabled); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, bool cudnn_enabled); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_and_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_and_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d95c3db8eb1251860413384d12fc8c6175d8e1b0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_and_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_bitwise_and_Tensor : 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/broadcast_to_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/broadcast_to_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ccd2d32256c73f30139e4e62b72e8c604c4d61b1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/broadcast_to_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 broadcast_to(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor broadcast_to_symint(const at::Tensor & self, c10::SymIntArrayRef size); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conj_physical_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conj_physical_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..617bc805032a1dc9e83f784aaf0cc7117b967bd7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conj_physical_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 conj_physical(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_backward_overrideable.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_backward_overrideable.h new file mode 100644 index 0000000000000000000000000000000000000000..dd42559783bdab4f12ef77889f8e849f2bdfbce1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_backward_overrideable.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::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) +inline ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask); + } +} + +// aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) +inline ::std::tuple convolution_backward_overrideable_symint(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_symint_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_backward_overrideable_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_backward_overrideable_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..12dce814d45553f1f1c2b34c8489f5a28ec9268f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_backward_overrideable_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 ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_overrideable_symint(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple convolution_backward_overrideable_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_overrideable_symint_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/crow_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/crow_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e7eef9e550737d2ec979f2ab0c661187cc47e94d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/crow_indices_copy_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor crow_indices_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..90593e4e3c8ca9f4e44a4864b92bb5890a1ef164 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/embedding_dense_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/embedding_dense_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..006d55e1c83b386b0901635cdd103063595eef60 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/embedding_dense_backward_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 & embedding_dense_backward_out_symint(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out); +TORCH_API at::Tensor embedding_dense_backward_cpu(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); +TORCH_API at::Tensor embedding_dense_backward_cuda(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/exp2.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/exp2.h new file mode 100644 index 0000000000000000000000000000000000000000..69fc615bc22b9cb64dde19b57fcd300c6c088ff3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/exp2.h @@ -0,0 +1,44 @@ +#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::exp2(Tensor self) -> Tensor +inline at::Tensor exp2(const at::Tensor & self) { + return at::_ops::exp2::call(self); +} + +// aten::exp2_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & exp2_(at::Tensor & self) { + return at::_ops::exp2_::call(self); +} + +// aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exp2_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::exp2_out::call(self, out); +} +// aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exp2_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::exp2_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..932db4f7adc8070d4b3253aaae92613aaa5243b7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.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::fbgemm_linear_int8_weight(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor +inline at::Tensor fbgemm_linear_int8_weight(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias) { + return at::_ops::fbgemm_linear_int8_weight::call(input, weight, packed, col_offsets, weight_scale, weight_zero_point, bias); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1a3ca662b32ffec219e226c197e8ec207fa117bc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/feature_dropout_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 feature_dropout(const at::Tensor & input, double p, bool train); +TORCH_API at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_hfftn_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_hfftn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bded18b232645a8fe518588989ce0e289df474f3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_hfftn_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 fft_hfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API const at::Tensor & fft_hfftn_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftn_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b72aef2d63dcb464af391b895c0f8574a5c2fbcc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftn_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 fft_ifftn { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_ifftn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ifftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm); +}; + +struct TORCH_API fft_ifftn_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_ifftn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ifftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fmin_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fmin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b669217e276ec59dd2a440841b458b1fe46d87d2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fmin_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 fmin { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fmin") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fmin(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API fmin_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fmin") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fmin.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geometric.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geometric.h new file mode 100644 index 0000000000000000000000000000000000000000..5706e2fe495f04fd9e42e9d26b051e018f6d305f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geometric.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::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & geometric_out(at::Tensor & out, const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::geometric_out::call(self, p, generator, out); +} +// aten::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & geometric_outf(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out) { + return at::_ops::geometric_out::call(self, p, generator, out); +} + +// aten::geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor +inline at::Tensor geometric(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::geometric::call(self, p, generator); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardshrink_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardshrink_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ad67e62930d4138924c3f1a7c9e86caf084f4ecd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardshrink_backward_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 +#include + +namespace at { +namespace native { +struct TORCH_API structured_hardshrink_backward_out : public at::meta::structured_hardshrink_backward { +void impl(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lerp_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lerp_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c236873f881c152b00dd9fe191329df719486f0a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lerp_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross_native.h new file mode 100644 index 0000000000000000000000000000000000000000..80c989b10499d558140947cee032f01fe61582bd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_linalg_cross_out : public at::meta::structured_linalg_cross { +void impl(const at::Tensor & self, const at::Tensor & other, int64_t dim, const at::Tensor & out); +}; +TORCH_API at::Tensor linalg_cross_zerotensor(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c098d179f1b3feea6955056343c0d9ab5aaf94e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_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 linalg_lu { + using schema = ::std::tuple (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::linalg_lu") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_lu(Tensor A, *, bool pivot=True) -> (Tensor P, Tensor L, Tensor U)") + static ::std::tuple call(const at::Tensor & A, bool pivot); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot); +}; + +struct TORCH_API linalg_lu_out { + using schema = ::std::tuple (const at::Tensor &, bool, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_lu") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_lu.out(Tensor A, *, bool pivot=True, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U)") + static ::std::tuple call(const at::Tensor & A, bool pivot, at::Tensor & P, at::Tensor & L, at::Tensor & U); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot, at::Tensor & P, at::Tensor & L, at::Tensor & U); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_solve_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_solve_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..81a0e5a951154c26590fa7b1ace0610f6d9f1462 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_solve_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor linalg_lu_solve(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..303f6841daeb573be3d4bdd12a9fbe60c335af9e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_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 +#include + +namespace at { +namespace native { +struct TORCH_API structured_logaddexp2_out : public at::meta::structured_logaddexp2 { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lstm_mps_backward_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lstm_mps_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..27a000c9bea2ae202910accaf1c1da45edebb7fc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lstm_mps_backward_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 void lstm_mps_backward_out(at::Tensor & out0, at::TensorList out1, at::TensorList out2, const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); +TORCH_API void lstm_mps_backward_outf(const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first, at::Tensor & out0, at::TensorList out1, at::TensorList out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matrix_power_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matrix_power_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..88f400387f104d9b806169e15e1a1ccfd8807b18 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matrix_power_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor matrix_power(const at::Tensor & self, int64_t n); +TORCH_API at::Tensor & matrix_power_out(at::Tensor & out, const at::Tensor & self, int64_t n); +TORCH_API at::Tensor & matrix_power_outf(const at::Tensor & self, int64_t n, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70cd5af6a0d02dddaf1155bae037fb60fe6153a1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_with_indices_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 ::std::tuple max_pool3d_with_indices(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API ::std::tuple max_pool3d_with_indices_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API ::std::tuple max_pool3d_with_indices_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/median_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/median_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c62be4ea2ba60569942e7a2fda138ef680f4063 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/median_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 median(const at::Tensor & self); +TORCH_API ::std::tuple median_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple median_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/min_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/min_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13032f04eaee9a0c35286f9e192437ebea2c9cbc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/min_cuda_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 cuda { + +TORCH_API ::std::tuple min(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple min_out(at::Tensor & min, at::Tensor & min_indices, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple min_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); +TORCH_API at::Tensor min(const at::Tensor & self); +TORCH_API at::Tensor & min_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & min_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_convolution_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fcb219b04b2fe6f40801c96708a559dd52c01ac1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_convolution_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 miopen_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::miopen_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +}; + +struct TORCH_API miopen_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, 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::miopen_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aa5b6f69bc7fb09fcef585ac3fddba47c80ada34 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e4a02d897dcd4320ba5148c2b72d88c5f701e7c6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor multi_margin_loss_cpu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cpu_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +TORCH_API at::Tensor multi_margin_loss_cuda_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cuda_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_channel_shuffle_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_channel_shuffle_native.h new file mode 100644 index 0000000000000000000000000000000000000000..85490fa13dc684f3cc0a645f7f949ed4932a0a02 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_channel_shuffle_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 math_channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor channel_shuffle_cpu(const at::Tensor & self, int64_t groups); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nonzero_numpy_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nonzero_numpy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..583ae4923ceccbde2d5df17767e2903806abd9f4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nonzero_numpy_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 nonzero_numpy { + using schema = ::std::vector (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::nonzero_numpy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero_numpy(Tensor self) -> Tensor[]") + static ::std::vector call(const at::Tensor & self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/pinverse_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/pinverse_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1ea30a2cc8bdd368b36431907c8fa899185ac3d8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/pinverse_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 pinverse { + using schema = at::Tensor (const at::Tensor &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::pinverse") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "pinverse(Tensor self, float rcond=1e-15) -> Tensor") + static at::Tensor call(const at::Tensor & self, double rcond); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double rcond); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/qr_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/qr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..250645765fe52ad65c22f9e4f20e048ce175a0c9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/qr_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 qr_Q { + using schema = ::std::tuple (const at::Tensor &, 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::qr") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Q") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "qr.Q(Tensor self, bool some=True, *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R)") + static ::std::tuple call(const at::Tensor & self, bool some, at::Tensor & Q, at::Tensor & R); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool some, at::Tensor & Q, at::Tensor & R); +}; + +struct TORCH_API qr { + using schema = ::std::tuple (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::qr") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "qr(Tensor self, bool some=True) -> (Tensor Q, Tensor R)") + static ::std::tuple call(const at::Tensor & self, bool some); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool some); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_gru_cell.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_gru_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..3344edc7e693f1d12af422fd0027f98a402f2ae9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_gru_cell.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::quantized_gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor +inline at::Tensor quantized_gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh) { + return at::_ops::quantized_gru_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh, packed_ih, packed_hh, col_offsets_ih, col_offsets_hh, scale_ih, scale_hh, zero_point_ih, zero_point_hh); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..17198c461d7589601555a9884a656ef64f4a4823 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_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::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); + } +} + +// aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); + } +} + +// aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, padding, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, padding, grad_input); + } +} + +// aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad3d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, padding, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad3d_backward_grad_input::call(grad_output, self, padding, grad_input); + } +} + +// aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor +inline at::Tensor replication_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d_backward::call(grad_output, self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template ::value>> + at::Tensor replication_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad3d_backward::call(grad_output, self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor +inline at::Tensor replication_pad3d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d_backward::call(grad_output, self, padding); +} +namespace symint { + template ::value>> + at::Tensor replication_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad3d_backward::call(grad_output, self, padding); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsub_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsub_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1015fc80e978a306fe9e83c12ff4c2241ff46715 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsub_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 rsub(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sgn_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sgn_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ac1f032f29b53adff3bbead4b66c17c0cb6ddb94 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sgn_cpu_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 cpu { + +TORCH_API at::Tensor sgn(const at::Tensor & self); +TORCH_API at::Tensor & sgn_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sgn_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sgn_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softmax_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..16ed380b90449e359bea0b8031fe0dd94b5915a6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softmax_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 softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csc_tensor_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csc_tensor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..993184371c3e2a5ce7939c8cd7d55d2e4ad43bb6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csc_tensor_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 sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::TensorOptions options); +TORCH_API at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_erfcx_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_erfcx_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..015d78ecb4175bd92d5ccce48fca6cc36a68b44d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_erfcx_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 special_erfcx(const at::Tensor & self); +TORCH_API at::Tensor & special_erfcx_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_erfcx_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..436f6477d177517f905e8a31d683860072909903 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_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_shifted_chebyshev_polynomial_v(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_v_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_v_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_v(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_v_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/std_mean_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_mean_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..94862248084b3008aafcbc0b4c9d3c41affa7a0b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_mean_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 std_mean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sum_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sum_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..ccd8d51b526318de67fe8ccd0a9a71b3903d5813 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sum_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_sum_dim_IntList : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_size_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..87b98db1bb8b19465105df22d7ceea633b7ee7f8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_size_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 sym_size_int { + using schema = c10::SymInt (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sym_size") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sym_size.int(Tensor self, int dim) -> SymInt") + static c10::SymInt call(const at::Tensor & self, int64_t dim); + static c10::SymInt redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take.h new file mode 100644 index 0000000000000000000000000000000000000000..aab62f0f3f8c0ba2d1636a67237b2baf124a6156 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/take.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.out(Tensor self, Tensor index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index) { + return at::_ops::take_out::call(self, index, out); +} +// aten::take.out(Tensor self, Tensor index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_outf(const at::Tensor & self, const at::Tensor & index, at::Tensor & out) { + return at::_ops::take_out::call(self, index, out); +} + +// aten::take(Tensor self, Tensor index) -> Tensor +inline at::Tensor take(const at::Tensor & self, const at::Tensor & index) { + return at::_ops::take::call(self, index); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_native.h new file mode 100644 index 0000000000000000000000000000000000000000..af97f5bfa3af722ab3fb1b36133401092aaf16b3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_threshold_out : public at::meta::structured_threshold { +void impl(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, const at::Tensor & out); +}; +TORCH_API at::Tensor threshold_quantized_cpu(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/transpose.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..550d075e668965c9e3a45e2e071edc7a37b173ed --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/transpose.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::transpose.int(Tensor(a) self, int dim0, int dim1) -> Tensor(a) +inline at::Tensor transpose(const at::Tensor & self, int64_t dim0, int64_t dim1) { + return at::_ops::transpose_int::call(self, dim0, dim1); +} + +// aten::transpose.Dimname(Tensor(a) self, Dimname dim0, Dimname dim1) -> Tensor(a) +inline at::Tensor transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1) { + return at::_ops::transpose_Dimname::call(self, dim0, dim1); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trapz.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trapz.h new file mode 100644 index 0000000000000000000000000000000000000000..7546724b412b034ec4b4d35ddd9116e2f865878b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trapz.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::trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor +inline at::Tensor trapz(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1) { + return at::_ops::trapz_x::call(y, x, dim); +} + +// aten::trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor +inline at::Tensor trapz(const at::Tensor & y, double dx=1, int64_t dim=-1) { + return at::_ops::trapz_dx::call(y, dx, dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9fd6424235f370d0201706626414b1b13bf92116 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cuda_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 cuda { + +TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_bicubic2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5bd39e525b92ec75e5b3a517a8718db041bf4d01 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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_upsample_bilinear2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36241b0998bb205ed76e8aec9cf811cc48df1162 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta_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 meta { + +TORCH_API at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bilinear2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_trilinear3d_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_trilinear3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c120647c37b3a0c11b5f2b8a839c5d3b76bcdefa --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_trilinear3d_meta_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 meta { + +TORCH_API at::Tensor upsample_trilinear3d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_trilinear3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_trilinear3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/where_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/where_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d0791419585e6f80cf67579b96a979af6022fdc9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/where_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 where_self { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::where") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "self") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "where.self(Tensor condition, Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API where_self_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::where") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "self_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API where_ScalarSelf { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, 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::where") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarSelf") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API where_ScalarOther { + 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::where") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarOther") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "where.ScalarOther(Tensor condition, Tensor self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API where_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::where") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "where.Scalar(Tensor condition, Scalar self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other); +}; + +struct TORCH_API where { + using schema = ::std::vector (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::where") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "where(Tensor condition) -> Tensor[]") + static ::std::vector call(const at::Tensor & condition); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition); +}; + +}} // namespace at::_ops