diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_addmm_activation_meta_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_addmm_activation_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4d211759a06dfba8323dcbc4ae9261f0096ff8ba --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_addmm_activation_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 _addmm_activation(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1, bool use_gelu=false); +TORCH_API at::Tensor & _addmm_activation_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1, bool use_gelu=false); +TORCH_API at::Tensor & _addmm_activation_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, bool use_gelu, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_conj_physical_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_conj_physical_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9a7db8a44d2501cceec25333fd1adc16226526d2 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_conj_physical_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 _conj_physical { + 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::_conj_physical") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_conj_physical(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _conj_physical_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_conj_physical") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_conv_depthwise2d_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_conv_depthwise2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..654bdc4e9f03558f47848c930229ce9d10e56597 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_conv_depthwise2d_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 conv_depthwise2d_cuda(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); +TORCH_API const at::Tensor & conv_depthwise2d_cuda_out(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, const at::Tensor & out); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7d9c1280be606d46f0dca7a109c1695decbf4963 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_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 void _cudnn_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API void _cudnn_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +TORCH_API void _cudnn_rnn_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API void _cudnn_rnn_backward_symint_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c.h new file mode 100644 index 0000000000000000000000000000000000000000..0f1c238ca828606862a4f3a432dcfcc8db699437 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_r2c.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::_fft_r2c(Tensor self, int[] dim, int normalization, bool onesided) -> Tensor +inline at::Tensor _fft_r2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided) { + return at::_ops::_fft_r2c::call(self, dim, normalization, onesided); +} + +// aten::_fft_r2c.out(Tensor self, int[] dim, int normalization, bool onesided, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_r2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided) { + return at::_ops::_fft_r2c_out::call(self, dim, normalization, onesided, out); +} +// aten::_fft_r2c.out(Tensor self, int[] dim, int normalization, bool onesided, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_r2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out) { + return at::_ops::_fft_r2c_out::call(self, dim, normalization, onesided, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bb28195bd50d01f3f9afe6f3c2a6510e1a98e5f0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_native.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_sub_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_sub_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_sub_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_sub_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_sub_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_sub_list_kernel_slow(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_sub_List_out(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +TORCH_API void foreach_tensor_sub_list_kernel_slow_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_sub_list_kernel_cuda(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_sub_list_kernel_cuda_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_sub_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_sub_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_sub_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_sub_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_sub_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_native.h new file mode 100644 index 0000000000000000000000000000000000000000..54444a979d83e0c047e780cb71bae471fba2d1f3 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_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 ::std::vector _foreach_zero(at::TensorList self); +TORCH_API void _foreach_zero_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_zero_slow_(at::TensorList self); +TORCH_API void foreach_tensor_zero_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_get_max_seqlen.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_get_max_seqlen.h new file mode 100644 index 0000000000000000000000000000000000000000..117e3f55dab1dad7e0bba0a80f033c1bfaedb072 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_get_max_seqlen.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::_nested_get_max_seqlen(Tensor self) -> Tensor +inline at::Tensor _nested_get_max_seqlen(const at::Tensor & self) { + return at::_ops::_nested_get_max_seqlen::call(self); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask.h new file mode 100644 index 0000000000000000000000000000000000000000..1c249ce60319256934f8ed40d54a71286ec7ab4c --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask.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::_nested_tensor_from_mask(Tensor t, Tensor mask, bool mask_check=True) -> Tensor +inline at::Tensor _nested_tensor_from_mask(const at::Tensor & t, const at::Tensor & mask, bool mask_check=true) { + return at::_ops::_nested_tensor_from_mask::call(t, mask, mask_check); +} + +// aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_mask_out(at::Tensor & out, const at::Tensor & t, const at::Tensor & mask, bool mask_check=true) { + return at::_ops::_nested_tensor_from_mask_out::call(t, mask, mask_check, out); +} +// aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_mask_outf(const at::Tensor & t, const at::Tensor & mask, bool mask_check, at::Tensor & out) { + return at::_ops::_nested_tensor_from_mask_out::call(t, mask, mask_check, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_packed_sequence_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_packed_sequence_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..495fba1114622c368a7fb90939635a325279a08d --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_packed_sequence_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 _pad_packed_sequence { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, const at::Scalar &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_pad_packed_sequence") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_pad_packed_sequence(Tensor data, Tensor batch_sizes, bool batch_first, Scalar padding_value, int total_length) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & data, const at::Tensor & batch_sizes, bool batch_first, const at::Scalar & padding_value, int64_t total_length); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & data, const at::Tensor & batch_sizes, bool batch_first, const at::Scalar & padding_value, int64_t total_length); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..258762ef6dd9a7cf4a799a4e9288d10cc11c9de4 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_attention_math_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 _scaled_dot_product_attention_math { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, double, bool, const ::std::optional &, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_scaled_dot_product_attention_math") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None, *, float? scale=None, bool enable_gqa=False) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, const ::std::optional & dropout_mask, ::std::optional scale, bool enable_gqa); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, const ::std::optional & dropout_mask, ::std::optional scale, bool enable_gqa); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_backward_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8805e0c47ff221db1c5ba32e882527c66056abe2 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_backward_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 ::std::tuple _scaled_dot_product_fused_attention_overrideable_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & attn_bias, ::std::array grad_input_mask, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5d12ba8b67a5879cf601b742a0d2f781e8286a47 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_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 _sparse_coo_tensor_with_dims_and_tensors { + using schema = at::Tensor (int64_t, int64_t, c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_coo_tensor_with_dims_and_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False, bool? is_coalesced=None) -> Tensor") + static at::Tensor call(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional is_coalesced); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional is_coalesced); +}; + +struct TORCH_API _sparse_coo_tensor_with_dims_and_tensors_out { + using schema = at::Tensor & (int64_t, int64_t, c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_coo_tensor_with_dims_and_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, bool? is_coalesced=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_test_warn_in_autograd.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_test_warn_in_autograd.h new file mode 100644 index 0000000000000000000000000000000000000000..279e321f51cbd03212c8c67aff0e88a8da85ad2b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_test_warn_in_autograd.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::_test_warn_in_autograd(Tensor self) -> Tensor +inline at::Tensor _test_warn_in_autograd(const at::Tensor & self) { + return at::_ops::_test_warn_in_autograd::call(self); +} + +// aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_warn_in_autograd_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_test_warn_in_autograd_out::call(self, out); +} +// aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_warn_in_autograd_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_test_warn_in_autograd_out::call(self, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..52e593741982994aa2934b6213aa96415e2cbd55 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_backward_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 _thnn_fused_lstm_cell_backward { + using schema = ::std::tuple (const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_thnn_fused_lstm_cell_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_thnn_fused_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0817cc589ae534208ae15696162b2c72057235c0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _upsample_nearest_exact2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_nearest_exact2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d7b046897e899255bd90b9543d469ea1c1549372 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface_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 _weight_norm_interface { + using schema = ::std::tuple (const at::Tensor &, 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::_weight_norm_interface") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & v, const at::Tensor & g, int64_t dim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & v, const at::Tensor & g, int64_t dim); +}; + +struct TORCH_API _weight_norm_interface_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, int64_t, 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::_weight_norm_interface") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca344b5ebe18466e734d683f09dda1cf55b87576 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_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 adaptive_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/adjoint_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/adjoint_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ac8b205aea41ffe3d436b1105e1d044e9710813 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/adjoint_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 adjoint(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/arange.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/arange.h new file mode 100644 index 0000000000000000000000000000000000000000..1bee7b7bb4a41d805be1d17734c9e7f9a31986cf --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/arange.h @@ -0,0 +1,70 @@ +#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::arange(Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor arange(const at::Scalar & end, at::TensorOptions options={}) { + return at::_ops::arange::call(end, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::arange(Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor arange(const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::arange::call(end, dtype, layout, device, pin_memory); +} + +// aten::arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, at::TensorOptions options={}) { + return at::_ops::arange_start::call(start, end, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::arange_start::call(start, end, dtype, layout, device, pin_memory); +} + +// aten::arange.start_step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::TensorOptions options={}) { + return at::_ops::arange_start_step::call(start, end, step, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::arange.start_step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::arange_start_step::call(start, end, step, dtype, layout, device, pin_memory); +} + +// aten::arange.out(Scalar end, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arange_out(at::Tensor & out, const at::Scalar & end) { + return at::_ops::arange_out::call(end, out); +} +// aten::arange.out(Scalar end, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arange_outf(const at::Scalar & end, at::Tensor & out) { + return at::_ops::arange_out::call(end, out); +} + +// aten::arange.start_out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arange_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step) { + return at::_ops::arange_start_out::call(start, end, step, out); +} +// aten::arange.start_out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arange_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out) { + return at::_ops::arange_start_out::call(start, end, step, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/arctanh_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/arctanh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cc74d29b879eb8376c06995774289e328f98f5f5 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/arctanh_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 arctanh { + 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::arctanh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "arctanh(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 arctanh_ { + 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::arctanh_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "arctanh_(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 arctanh_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::arctanh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "arctanh.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/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/atanh.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/atanh.h new file mode 100644 index 0000000000000000000000000000000000000000..5254002a82b6a8192e924115d3bb4f645ff99f43 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/atanh.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::atanh(Tensor self) -> Tensor +inline at::Tensor atanh(const at::Tensor & self) { + return at::_ops::atanh::call(self); +} + +// aten::atanh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & atanh_(at::Tensor & self) { + return at::_ops::atanh_::call(self); +} + +// aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::atanh_out::call(self, out); +} +// aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::atanh_out::call(self, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ce4a975bd0c467f2970965ec899df29ad17db3df --- /dev/null +++ b/vllm/lib/python3.10/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/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bernoulli_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bernoulli_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0c9b296b7033ac2cbcec402079a6503ac7284a2a --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bernoulli_native.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor bernoulli(const at::Tensor & self, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & bernoulli_out(const at::Tensor & self, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor bernoulli(const at::Tensor & self, const at::Tensor & p, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & bernoulli_Tensor_out(const at::Tensor & self, const at::Tensor & p, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & bernoulli_(at::Tensor & self, const at::Tensor & p, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & bernoulli_float_out(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & bernoulli_(at::Tensor & self, double p=0.5, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor bernoulli(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1489472c1ada3d05bcb11c06ffb562551bd9b4f4 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor bitwise_and(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_and_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/chunk_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/chunk_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ee112f074ba1b4a8cf1c095ee47d59636d35facd --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/chunk_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::vector chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b39437a3ecc583d88d07439d820ecfedc32a8b0f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & col_indices_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor col_indices_copy(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/dense_dim_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/dense_dim_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..92f7c65644bfd5ed82499b6aac475bed04448cb5 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/dense_dim_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 dense_dim { + using schema = int64_t (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::dense_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "dense_dim(Tensor self) -> int") + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/dsplit_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/dsplit_native.h new file mode 100644 index 0000000000000000000000000000000000000000..26b979184868a71d3f7e7f05c82fb46996e989b6 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/dsplit_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 ::std::vector dsplit(const at::Tensor & self, int64_t sections); +TORCH_API ::std::vector dsplit(const at::Tensor & self, at::IntArrayRef indices); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/eq_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/eq_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aa39017b8e154f68ea56b27bb32c14a36c716e23 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/eq_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 eq(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & eq_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & eq_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor eq(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & eq_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & eq_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation.h new file mode 100644 index 0000000000000000000000000000000000000000..d03ca3a4725ef966cf3331ee3e5e9629d0679bb1 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation.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_fp32_activation(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_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias) { + return at::_ops::fbgemm_linear_int8_weight_fp32_activation::call(input, weight, packed, col_offsets, weight_scale, weight_zero_point, bias); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5751b6c0bc7c489e8da0447a8af96f01a65c58c9 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_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_rfft2 { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_rfft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_rfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm); +}; + +struct TORCH_API fft_rfft2_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_rfft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_rfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gcd_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gcd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..446db7321ad862e0ccf56669b39fa4e865cd379d --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gcd_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_gcd_out : public at::meta::structured_gcd { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gradient_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gradient_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5824553346d1bbb91e526983e02c21dbb1256d17 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gradient_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::vector gradient(const at::Tensor & self, const ::std::optional & spacing=::std::nullopt, ::std::optional dim=::std::nullopt, int64_t edge_order=1); +TORCH_API ::std::vector gradient(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order=1); +TORCH_API ::std::vector gradient(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order=1); +TORCH_API ::std::vector gradient(const at::Tensor & self, at::ArrayRef spacing, ::std::optional dim=::std::nullopt, int64_t edge_order=1); +TORCH_API ::std::vector gradient(const at::Tensor & self, at::ArrayRef spacing, at::IntArrayRef dim, int64_t edge_order=1); +TORCH_API ::std::vector gradient(const at::Tensor & self, at::TensorList spacing, ::std::optional dim=::std::nullopt, int64_t edge_order=1); +TORCH_API ::std::vector gradient(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order=1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63c9f8cfa49edd9df9ceea4ea2dc24f23119aaba --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_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 grid_sampler { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::grid_sampler") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "grid_sampler(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/hardtanh_backward_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/hardtanh_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..46aae89384310e93a51ad04c0626b6c782ad745c --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/hardtanh_backward_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 hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val); +TORCH_API at::Tensor & hardtanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val); +TORCH_API at::Tensor & hardtanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/index_reduce_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/index_reduce_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3e074e1bbba4d104f52e478611eb19d0ce0f65ec --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/index_reduce_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_index_reduce_cpu_out : public at::meta::structured_index_reduce { +void impl(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self, const at::Tensor & out); +}; +struct TORCH_API structured_index_reduce_cuda_out : public at::meta::structured_index_reduce { +void impl(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/index_select_backward_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/index_select_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc81d1b303dc5d807548ea9dc781504388ed5960 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/index_select_backward_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 index_select_backward(const at::Tensor & grad, at::IntArrayRef self_sizes, int64_t dim, const at::Tensor & index); +TORCH_API at::Tensor index_select_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef self_sizes, int64_t dim, const at::Tensor & index); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lift_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lift_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..abd012fd391dc43e1847a657cc9b6f62f7a95512 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lift_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor lift(const at::Tensor & self); +TORCH_API at::Tensor & lift_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & lift_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..13cb333f72427c1f4ebff7ec460af62653dc85a8 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_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_cholesky { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_cholesky") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_cholesky(Tensor self, *, bool upper=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool upper); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper); +}; + +struct TORCH_API linalg_cholesky_out { + using schema = at::Tensor & (const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_cholesky") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_cholesky.out(Tensor self, *, bool upper=False, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, bool upper, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9b74f9aec1da4fc6a5d5060dee1704b5bea050de --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_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_linalg_ldl_factor_ex_out : public at::meta::structured_linalg_ldl_factor_ex { +void impl(const at::Tensor & self, bool hermitian, bool check_errors, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & info); +}; +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64a0949f1f4ecee5f38aef449204a44c50ee785b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple linalg_lu(const at::Tensor & A, bool pivot=true); +TORCH_API ::std::tuple linalg_lu_out(at::Tensor & P, at::Tensor & L, at::Tensor & U, const at::Tensor & A, bool pivot=true); +TORCH_API ::std::tuple linalg_lu_outf(const at::Tensor & A, bool pivot, at::Tensor & P, at::Tensor & L, at::Tensor & U); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_meta.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..516271a86276590fbfe15c72a66593448eed1e07 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_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_linalg_lu : public at::impl::MetaBase { + + + void meta(const at::Tensor & A, bool pivot); +}; + +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_or.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_or.h new file mode 100644 index 0000000000000000000000000000000000000000..30134517321a51f9e3f195a020c69f715ec4f4f3 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_or.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::logical_or(Tensor self, Tensor other) -> Tensor +inline at::Tensor logical_or(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logical_or::call(self, other); +} + +// aten::logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logical_or_out::call(self, other, out); +} +// aten::logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::logical_or_out::call(self, other, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_xor.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_xor.h new file mode 100644 index 0000000000000000000000000000000000000000..2e53164fb8198d0947f0b664d489733c95d3da04 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_xor.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::logical_xor(Tensor self, Tensor other) -> Tensor +inline at::Tensor logical_xor(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logical_xor::call(self, other); +} + +// aten::logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::logical_xor_out::call(self, other, out); +} +// aten::logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & logical_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::logical_xor_out::call(self, other, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_xor_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_xor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..12031eb68e7525b6dca1555b2696ede3c40dac73 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/logical_xor_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 logical_xor { + 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::logical_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logical_xor(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API logical_xor_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logical_xor_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logical_xor_(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API logical_xor_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::logical_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logical_xor.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/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/masked_select_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/masked_select_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc97d901e679b75ff979c0b1f6b4710c33a29c91 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/masked_select_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 masked_select(const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & masked_select_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & masked_select_outf(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3741e1fcc10dc6bae759a6ddc1e950c2f79a7123 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_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 max(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple max_out(at::Tensor & max, at::Tensor & max_values, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple max_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values); +TORCH_API at::Tensor max(const at::Tensor & self); +TORCH_API at::Tensor & max_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & max_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_unpool2d.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_unpool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..f6065e1f1b64c6447a6b25dd931a111932259a9f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_unpool2d.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::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template ::value>> + at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template ::value>> + at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); + } +} + +// aten::max_unpool2d.out(Tensor self, Tensor indices, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & max_unpool2d_symint_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::max_unpool2d_out::call(self, indices, output_size, out); + } +} + +// aten::max_unpool2d(Tensor self, Tensor indices, SymInt[2] output_size) -> Tensor +inline at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, c10::fromIntArrayRefSlow(output_size)); +} +namespace symint { + template ::value>> + at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, c10::fromIntArrayRefSlow(output_size)); + } +} + +// aten::max_unpool2d(Tensor self, Tensor indices, SymInt[2] output_size) -> Tensor +inline at::Tensor max_unpool2d_symint(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, output_size); +} +namespace symint { + template ::value>> + at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size) { + return at::_ops::max_unpool2d::call(self, indices, output_size); + } +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..73663ade8bdfe91372ae7254398c5725c6017d59 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor mvlgamma(const at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_(at::Tensor & self, int64_t p); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..18492212591558a0978c6e00635cb4c0d536b3ac --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple native_layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_symint(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_numpy_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_numpy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f4133a6aff68eb86bddb14ab2588ad21718805be --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_numpy_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 ::std::vector nonzero_numpy(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_static_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_static_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..efba203771eafe79f1426edb0293824cfc1ff7fb --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_static_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 nonzero_static_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nonzero_static") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero_static.out(Tensor self, *, int size, int fill_value=-1, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t size, int64_t fill_value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t size, int64_t fill_value, at::Tensor & out); +}; + +struct TORCH_API nonzero_static { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nonzero_static") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero_static(Tensor self, *, int size, int fill_value=-1) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t size, int64_t fill_value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t size, int64_t fill_value); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/not_equal_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/not_equal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b76d118bdb2042372005fd9e5dcb544344977fee --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/not_equal_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor not_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & not_equal_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & not_equal_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor not_equal(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & not_equal_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & not_equal_(at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..85a5ed928bde4c16aa56f83266d5b14c76724862 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor quantized_rnn_tanh_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rad2deg_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rad2deg_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..805558d8427bff383ef6f595d27e927f9c02bb6b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rad2deg_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 rad2deg { + 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::rad2deg") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rad2deg(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API rad2deg_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rad2deg_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rad2deg_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API rad2deg_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rad2deg") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rad2deg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4465aa774fce171038b5677c963def97ae61a5bf --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_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 replication_pad2d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad2d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/result_type.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/result_type.h new file mode 100644 index 0000000000000000000000000000000000000000..33426c56b0f7e50bf024f682f865f7d05c484d2c --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/result_type.h @@ -0,0 +1,45 @@ +#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::result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType +inline at::ScalarType result_type(const at::Tensor & tensor, const at::Tensor & other) { + return at::_ops::result_type_Tensor::call(tensor, other); +} + +// aten::result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType +inline at::ScalarType result_type(const at::Tensor & tensor, const at::Scalar & other) { + return at::_ops::result_type_Scalar::call(tensor, other); +} + +// aten::result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType +inline at::ScalarType result_type(const at::Scalar & scalar, const at::Tensor & tensor) { + return at::_ops::result_type_Scalar_Tensor::call(scalar, tensor); +} + +// aten::result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType +inline at::ScalarType result_type(const at::Scalar & scalar1, const at::Scalar & scalar2) { + return at::_ops::result_type_Scalar_Scalar::call(scalar1, scalar2); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rnn_tanh_cell.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rnn_tanh_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..bd090f10e27db9d498d520721f8fc1ca11f1ea53 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rnn_tanh_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::rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor +inline at::Tensor rnn_tanh_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_hh={}) { + return at::_ops::rnn_tanh_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/roll_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/roll_native.h new file mode 100644 index 0000000000000000000000000000000000000000..af63d87ba2924624024bff6d1b4495de1b8582ac --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/roll_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 & roll_out_symint(const at::Tensor & self, c10::SymIntArrayRef shifts, at::IntArrayRef dims, at::Tensor & out); +TORCH_API at::Tensor roll(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}); +TORCH_API at::Tensor roll_cuda(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/row_stack_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/row_stack_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9fe8b31fcfee97c14cf0206cc02d675ab03bfda0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/row_stack_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 row_stack { + using schema = at::Tensor (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::row_stack") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "row_stack(Tensor[] tensors) -> Tensor") + static at::Tensor call(at::TensorList tensors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +struct TORCH_API row_stack_out { + using schema = at::Tensor & (at::TensorList, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::row_stack") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "row_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(at::TensorList tensors, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8cb51b0729e44aa2bf16bf23f980c3a116a3054f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor rrelu_with_noise_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result); +TORCH_API at::Tensor & rrelu_with_noise_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result); +TORCH_API at::Tensor & rrelu_with_noise_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/select_copy.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/select_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..acde0dede9385fd644fd9f224c83a5f4fe55bdbe --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/select_copy.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::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor +inline at::Tensor select_copy(const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int::call(self, dim, index); +} +namespace symint { + template ::value>> + at::Tensor select_copy(const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int::call(self, dim, index); + } +} + +// aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor +inline at::Tensor select_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int::call(self, dim, index); +} +namespace symint { + template ::value>> + at::Tensor select_copy(const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int::call(self, dim, index); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +// aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_copy_symint_outf(const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_copy_int_out::call(self, dim, index, out); + } +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sgn_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sgn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4cc2b59e8a40894bdda1aa9b2c94700c1eaccdd4 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sgn_native.h @@ -0,0 +1,31 @@ +#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_sgn_out : public at::meta::structured_sgn { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_sgn(const at::Tensor & self); +TORCH_API at::Tensor & NestedTensor_sgn_(at::Tensor & self); +TORCH_API at::Tensor sgn_sparse(const at::Tensor & self); +TORCH_API at::Tensor & sgn_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sgn_sparse_(at::Tensor & self); +TORCH_API at::Tensor sgn_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & sgn_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sgn_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/signbit_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/signbit_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eecd921d7307e9c76edce50cdc87a0f093210b64 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/signbit_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 signbit(const at::Tensor & self); +TORCH_API at::Tensor & signbit_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & signbit_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/silu.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/silu.h new file mode 100644 index 0000000000000000000000000000000000000000..1d0f5b7a3310b6eaccdf2b383a21bbb113f61dbe --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/silu.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::silu(Tensor self) -> Tensor +inline at::Tensor silu(const at::Tensor & self) { + return at::_ops::silu::call(self); +} + +// aten::silu_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & silu_(at::Tensor & self) { + return at::_ops::silu_::call(self); +} + +// aten::silu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & silu_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::silu_out::call(self, out); +} +// aten::silu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & silu_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::silu_out::call(self, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_compressed_tensor_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_compressed_tensor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..048b22bcf2209b78e492713a62f4c23cb77fe92b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_compressed_tensor_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 sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor sparse_compressed_tensor_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor sparse_compressed_tensor_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::TensorOptions options); +TORCH_API at::Tensor sparse_compressed_tensor(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..355d7b71efdb5a201f7deba1bf7a1168f14d6620 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_chebyshev_polynomial_u(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_u_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a46c656a48a1972ec94af694b5779be129ca206b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_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 special_digamma { + 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::special_digamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_digamma(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_digamma_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_digamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e60f2a97e87050629c1cb064a4c3bd00b5d9649b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_ndtri(const at::Tensor & self); +TORCH_API at::Tensor & special_ndtri_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_ndtri_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sym_numel.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sym_numel.h new file mode 100644 index 0000000000000000000000000000000000000000..bf5e612f9b14791f9ace54ed8041a34c682ad990 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sym_numel.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::sym_numel(Tensor self) -> SymInt +inline c10::SymInt __dispatch_sym_numel(const at::Tensor & self) { + return at::_ops::sym_numel::call(self); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/t.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/t.h new file mode 100644 index 0000000000000000000000000000000000000000..05c4d9d5b802d7d6371bde31f3973a6eb29eda61 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/t.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::t(Tensor(a) self) -> Tensor(a) +inline at::Tensor t(const at::Tensor & self) { + return at::_ops::t::call(self); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/threshold_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/threshold_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e9cd00316162a88be44e58fa62e8bd687f8edfdf --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/threshold_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 threshold { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::threshold") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "threshold(Tensor self, Scalar threshold, Scalar value) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +}; + +struct TORCH_API threshold_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::threshold_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "threshold_(Tensor(a!) self, Scalar threshold, Scalar value) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +}; + +struct TORCH_API threshold_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::threshold") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "threshold.out(Tensor self, Scalar threshold, Scalar value, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..c898ea3b60ab5b7d7530185190e6cafd06bca053 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy.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::unbind_copy.int(Tensor self, int dim=0) -> Tensor[] +inline ::std::vector unbind_copy(const at::Tensor & self, int64_t dim=0) { + return at::_ops::unbind_copy_int::call(self, dim); +} + +// aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () +inline void unbind_copy_out(at::TensorList out, const at::Tensor & self, int64_t dim=0) { + return at::_ops::unbind_copy_int_out::call(self, dim, out); +} +// aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () +inline void unbind_copy_outf(const at::Tensor & self, int64_t dim, at::TensorList out) { + return at::_ops::unbind_copy_int_out::call(self, dim, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_meta.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..9180f967c26f0712c0c4651c15cd495111a58f4d --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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_trilinear3d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +} // namespace native +} // namespace at