diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e1380282531122ab0d813d32e5dd5bd8ec1fc01 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor _adaptive_avg_pool3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale.h new file mode 100644 index 0000000000000000000000000000000000000000..e044f02b699f07067a8db810dc8e6640e08b2d73 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_amp_foreach_non_finite_check_and_unscale.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::_amp_foreach_non_finite_check_and_unscale_(Tensor(a!)[] self, Tensor(b!) found_inf, Tensor inv_scale) -> () +inline void _amp_foreach_non_finite_check_and_unscale_(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale) { + return at::_ops::_amp_foreach_non_finite_check_and_unscale_::call(self, found_inf, inv_scale); +} + +// aten::_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> () +inline void _amp_foreach_non_finite_check_and_unscale_out(at::TensorList out, at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale) { + return at::_ops::_amp_foreach_non_finite_check_and_unscale_out::call(self, found_inf, inv_scale, out); +} +// aten::_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> () +inline void _amp_foreach_non_finite_check_and_unscale_outf(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale, at::TensorList out) { + return at::_ops::_amp_foreach_non_finite_check_and_unscale_out::call(self, found_inf, inv_scale, out); +} + +// aten::_amp_foreach_non_finite_check_and_unscale(Tensor[] self, Tensor found_inf, Tensor inv_scale) -> (Tensor[] self_out, Tensor found_inf_out) +inline ::std::tuple<::std::vector,at::Tensor> _amp_foreach_non_finite_check_and_unscale(at::TensorList self, const at::Tensor & found_inf, const at::Tensor & inv_scale) { + return at::_ops::_amp_foreach_non_finite_check_and_unscale::call(self, found_inf, inv_scale); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_batch_norm_no_update.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_batch_norm_no_update.h new file mode 100644 index 0000000000000000000000000000000000000000..cf1d3f086a11b8f3c32104cea461a831bff454a8 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_batch_norm_no_update.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::_batch_norm_no_update(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _batch_norm_no_update(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps) { + return at::_ops::_batch_norm_no_update::call(input, weight, bias, running_mean, running_var, momentum, eps); +} + +// aten::_batch_norm_no_update.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple _batch_norm_no_update_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps) { + return at::_ops::_batch_norm_no_update_out::call(input, weight, bias, running_mean, running_var, momentum, eps, out0, out1, out2, out3); +} +// aten::_batch_norm_no_update.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, float momentum, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple _batch_norm_no_update_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::_batch_norm_no_update_out::call(input, weight, bias, running_mean, running_var, momentum, eps, out0, out1, out2, out3); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Char_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Char_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7ecde69c246125ec003dbe6910f1815281289bab --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Char_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cast_Char { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cast_Char") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cast_Char(Tensor self, bool non_blocking=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool non_blocking); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a41c2286e93e8946ecf69248355846b14c761d1 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_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 & _coalesce_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & _coalesce_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/_cufft_get_plan_cache_size_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5fafbcdec1593de4b5a5509005a806efbeb4fbcd --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_size_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cufft_get_plan_cache_size { + using schema = int64_t (at::DeviceIndex); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cufft_get_plan_cache_size") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cufft_get_plan_cache_size(DeviceIndex device_index) -> int") + static int64_t call(at::DeviceIndex device_index); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, at::DeviceIndex device_index); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c9a68f4cf25d589bfafeaa141e1221e5faa2a6e --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_functional_sym_constrain_range_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 _functional_sym_constrain_range(const at::Scalar & size, ::std::optional min, ::std::optional max, const at::Tensor & dep_token); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd26ea462d90b3085d37e090bc2ae5a57eecabac --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_sgd_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_sgd(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_outf(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector> _fused_sgd(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_outf(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f46e559186543cee851c4547255e18965f87142a --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_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 & _fw_primal_copy_out(const at::Tensor & self, int64_t level, at::Tensor & out); +TORCH_API at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_logcumsumexp_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_logcumsumexp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0023da0522e1b03a80693095fe738a38a3823700 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_logcumsumexp_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 _logcumsumexp { + using schema = 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::_logcumsumexp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_logcumsumexp(Tensor self, int dim) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +struct TORCH_API _logcumsumexp_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_logcumsumexp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_logcumsumexp.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_compute_contiguous_strides_offsets.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_compute_contiguous_strides_offsets.h new file mode 100644 index 0000000000000000000000000000000000000000..742273f596dc71bcca82d3ebdf898f344b8aad44 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_compute_contiguous_strides_offsets.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_compute_contiguous_strides_offsets(Tensor nested_size) -> (Tensor, Tensor) +inline ::std::tuple _nested_compute_contiguous_strides_offsets(const at::Tensor & nested_size) { + return at::_ops::_nested_compute_contiguous_strides_offsets::call(nested_size); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list.h new file mode 100644 index 0000000000000000000000000000000000000000..b90534f8e1d9107658dcad2694cdc69d2f3e7de6 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list.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_tensor_list(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _nested_tensor_from_tensor_list(at::TensorList list, ::std::optional dtype=::std::nullopt, ::std::optional layout=::std::nullopt, ::std::optional device=::std::nullopt, ::std::optional pin_memory=::std::nullopt) { + return at::_ops::_nested_tensor_from_tensor_list::call(list, dtype, layout, device, pin_memory); +} + +// aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_tensor_list_out(at::Tensor & out, at::TensorList list, ::std::optional dtype=::std::nullopt, ::std::optional layout=::std::nullopt, ::std::optional device=::std::nullopt, ::std::optional pin_memory=::std::nullopt) { + return at::_ops::_nested_tensor_from_tensor_list_out::call(list, dtype, layout, device, pin_memory, out); +} +// aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_tensor_list_outf(at::TensorList list, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, at::Tensor & out) { + return at::_ops::_nested_tensor_from_tensor_list_out::call(list, dtype, layout, device, pin_memory, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_pdist_forward_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_pdist_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a6e98ecfa642f3790c5f84eb12fcff650ca56976 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_pdist_forward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _pdist_forward(const at::Tensor & self, double p=2); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_propagate_xla_data.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_propagate_xla_data.h new file mode 100644 index 0000000000000000000000000000000000000000..99d26a7aceda106231d6389d143ae9817c95490f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_propagate_xla_data.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::_propagate_xla_data(Tensor input, Tensor output) -> () +inline void _propagate_xla_data(const at::Tensor & input, const at::Tensor & output) { + return at::_ops::_propagate_xla_data::call(input, output); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..a15bbe89b9bf8545c5758e1238867382fb1983ad --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_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::_reshape_alias_copy(Tensor self, SymInt[] size, SymInt[] stride) -> Tensor +inline at::Tensor _reshape_alias_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); +} +namespace symint { + template ::value>> + at::Tensor _reshape_alias_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); + } +} + +// aten::_reshape_alias_copy(Tensor self, SymInt[] size, SymInt[] stride) -> Tensor +inline at::Tensor _reshape_alias_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, size, stride); +} +namespace symint { + template ::value>> + at::Tensor _reshape_alias_copy(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, size, stride); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); + } +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fade59258aa316f3ad1b54c9970a94811f037cc3 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable_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(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias={}, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..577ef30cc78b35c499f4148fcdfa6ceb5885daf9 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_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 _softmax { + using schema = at::Tensor (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_softmax(Tensor self, int dim, bool half_to_float) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, bool half_to_float); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float); +}; + +struct TORCH_API _softmax_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_unsafe_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_unsafe_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7fc1f0ed8f8cbae1824c3c2d08e90abbed808d06 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_unsafe_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_coo_tensor_unsafe { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, ::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_unsafe") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool? is_coalesced=None) -> Tensor") + static at::Tensor call(const at::Tensor & indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional is_coalesced); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional is_coalesced); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f33e2db982c16ff6fbb4cdb4b3cdbda7cfa50dc7 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_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 _sparse_mm_reduce_impl_sparse_csr_cpu(const at::Tensor & self, const at::Tensor & other, c10::string_view reduce); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d867f5e8a03f78288af7e7052916b4f63ef6da3a --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _sparse_sparse_matmul_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor sparse_sparse_matmul_cpu(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor sparse_sparse_matmul_cuda(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_stack_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_stack_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..98e3e4f963772389c2d0837c953540994d6c0f03 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_stack_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 _stack(at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & _stack_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & _stack_outf(at::TensorList tensors, int64_t dim, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02a1859489c7efddfe672dab79cdcf62e9ecc37e --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv_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 ::std::tuple _transform_bias_rescale_qkv_out(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple transform_bias_rescale_qkv_cpu(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads); +TORCH_API ::std::tuple transform_bias_rescale_qkv_cuda(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_unique_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_unique_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a85e9f6228e72c145573059ea367cf4408abbe0d --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_unique_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 ::std::tuple _unique_out(const at::Tensor & self, bool sorted, bool return_inverse, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple _unique_cpu(const at::Tensor & self, bool sorted=true, bool return_inverse=false); +TORCH_API ::std::tuple _unique_cuda(const at::Tensor & self, bool sorted=true, bool return_inverse=false); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_unpack_dual_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_unpack_dual_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dd35e468215e6bfadbcb2398e866c0ed0f1f85e5 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/_unpack_dual_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 _unpack_dual { + using schema = ::std::tuple (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::_unpack_dual") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent)") + static ::std::tuple call(const at::Tensor & dual, int64_t level); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dual, int64_t level); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0fae759f5d6d9051c7c7f0a81285e2a4b21cedd7 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_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_addcdiv_out : public at::meta::structured_addcdiv { +void impl(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/atleast_3d_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/atleast_3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2f31d754f92841054c0352496efa880635d4d5a3 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/atleast_3d_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 atleast_3d { + 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::atleast_3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "atleast_3d(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 atleast_3d_Sequence { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::atleast_3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Sequence") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "atleast_3d.Sequence(Tensor[] tensors) -> Tensor[]") + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_meta.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e399959085f886a4d2ce0fbcd58d7c0c6f5c3d7c --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_meta.h @@ -0,0 +1,114 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_avg_pool2d : public at::impl::MetaBase { + + template + struct TORCH_API precompute_out { + + precompute_out set_kH(int64_t value) { + static_assert(KH == false, "kH already set"); + precompute_out ret; +ret.kH = value; +ret.kW = this->kW; +ret.dH = this->dH; +ret.dW = this->dW; +ret.padH = this->padH; +ret.padW = this->padW; +return ret; + } + + + precompute_out set_kW(int64_t value) { + static_assert(KW == false, "kW already set"); + precompute_out ret; +ret.kH = this->kH; +ret.kW = value; +ret.dH = this->dH; +ret.dW = this->dW; +ret.padH = this->padH; +ret.padW = this->padW; +return ret; + } + + + precompute_out set_dH(int64_t value) { + static_assert(DH == false, "dH already set"); + precompute_out ret; +ret.kH = this->kH; +ret.kW = this->kW; +ret.dH = value; +ret.dW = this->dW; +ret.padH = this->padH; +ret.padW = this->padW; +return ret; + } + + + precompute_out set_dW(int64_t value) { + static_assert(DW == false, "dW already set"); + precompute_out ret; +ret.kH = this->kH; +ret.kW = this->kW; +ret.dH = this->dH; +ret.dW = value; +ret.padH = this->padH; +ret.padW = this->padW; +return ret; + } + + + precompute_out set_padH(int64_t value) { + static_assert(PADH == false, "padH already set"); + precompute_out ret; +ret.kH = this->kH; +ret.kW = this->kW; +ret.dH = this->dH; +ret.dW = this->dW; +ret.padH = value; +ret.padW = this->padW; +return ret; + } + + + precompute_out set_padW(int64_t value) { + static_assert(PADW == false, "padW already set"); + precompute_out ret; +ret.kH = this->kH; +ret.kW = this->kW; +ret.dH = this->dH; +ret.dW = this->dW; +ret.padH = this->padH; +ret.padW = value; +return ret; + } + + int64_t kH; +int64_t kW; +int64_t dH; +int64_t dW; +int64_t padH; +int64_t padW; + }; + using meta_return_ty = precompute_out ; + meta_return_ty meta(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +}; + +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..40ef58f08d75373b4d24b4bbf47774173b241ae2 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc63ebf8a3958bd16a58ae4c5f3a1c338a422845 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple batch_norm_backward_reduce(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_meta_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3652b5375ddd166cbb917629c4c0a29949e0536b --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor 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 meta +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c952a1ba1ae6ae7547b6fd202321777a1862d3d7 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c73c3a91fc3792f03300f0ec6a97e7b22c2218a --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/clone.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/clone.h new file mode 100644 index 0000000000000000000000000000000000000000..0198b6aa048743753741fe9bfb71000075f68de6 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/clone.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::clone(Tensor self, *, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt) { + return at::_ops::clone::call(self, memory_format); +} + +// aten::clone.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clone_out(at::Tensor & out, const at::Tensor & self, ::std::optional memory_format=::std::nullopt) { + return at::_ops::clone_out::call(self, memory_format, out); +} +// aten::clone.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & clone_outf(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::clone_out::call(self, memory_format, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/clone_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/clone_native.h new file mode 100644 index 0000000000000000000000000000000000000000..df5bbff10f6a956c9deeb978790a79be8cc368ba --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/clone_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & clone_out(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor clone_nested(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor clone_sparse(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor clone_sparse_compressed(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor mkldnn_clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor quantized_clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/col2im_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/col2im_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..072785412e57ce5e9cf8ffbbd686e194ca441004 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/col2im_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 col2im(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor col2im_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_outf(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor & col2im_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse.h new file mode 100644 index 0000000000000000000000000000000000000000..d728e7d08de34cb4179d590570ba0481e960d582 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse.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::copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!) +inline at::Tensor & copy_sparse_to_sparse_(at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_sparse_to_sparse_::call(self, src, non_blocking); +} + +// aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copy_sparse_to_sparse_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_sparse_to_sparse_out::call(self, src, non_blocking, out); +} +// aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copy_sparse_to_sparse_outf(const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out) { + return at::_ops::copy_sparse_to_sparse_out::call(self, src, non_blocking, out); +} + +// aten::copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor +inline at::Tensor copy_sparse_to_sparse(const at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_sparse_to_sparse::call(self, src, non_blocking); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/elu_backward_meta.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/elu_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5ff300e425a465de62db33545f50fa03a4a2ef9f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/elu_backward_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_elu_backward : public TensorIteratorBase { + + + void meta(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); +}; + +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/expm1_meta_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/expm1_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d4755b1a20f34e35b0efff99d5878c735fb4030f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/expm1_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor expm1(const at::Tensor & self); +TORCH_API at::Tensor & expm1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & expm1_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & expm1_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft.h new file mode 100644 index 0000000000000000000000000000000000000000..27afdaf3f5695f4a5557d560056070f8a981487e --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_fft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor +inline at::Tensor fft_fft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_fft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_fft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor +inline at::Tensor fft_fft_symint(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft::call(self, n, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_fft(const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft::call(self, n, dim, norm); + } +} + +// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft_out::call(self, n, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional n=::std::nullopt, int64_t dim=-1, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft_out::call(self, n, dim, norm, out); + } +} + +// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft_symint_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft_out::call(self, n, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft_out::call(self, n, dim, norm, out); + } +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f6b84db276ab61ad4c78029ad81b9b7093b69df7 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2_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_hfft2 { + 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_hfft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_hfft2(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_hfft2_out { + using schema = const at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional, 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::fft_hfft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static const at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, const at::Tensor & out); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, const at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/flatten_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/flatten_native.h new file mode 100644 index 0000000000000000000000000000000000000000..79c201f66fe7efff331ccf8c9d28997f1d69b0cc --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/flatten_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor flatten(const at::Tensor & self, int64_t start_dim=0, int64_t end_dim=-1); +TORCH_API at::Tensor flatten(const at::Tensor & self, int64_t start_dim, int64_t end_dim, at::Dimname out_dim); +TORCH_API at::Tensor flatten(const at::Tensor & self, at::Dimname start_dim, at::Dimname end_dim, at::Dimname out_dim); +TORCH_API at::Tensor flatten(const at::Tensor & self, at::DimnameList dims, at::Dimname out_dim); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/ge.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/ge.h new file mode 100644 index 0000000000000000000000000000000000000000..34cc41531f0b2625a996cc8d9228ff8064c23444 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/ge.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::ge.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::ge_Scalar_out::call(self, other, out); +} +// aten::ge.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::ge_Scalar_out::call(self, other, out); +} + +// aten::ge.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor ge(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::ge_Scalar::call(self, other); +} + +// aten::ge.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::ge_Tensor_out::call(self, other, out); +} +// aten::ge.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::ge_Tensor_out::call(self, other, out); +} + +// aten::ge.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor ge(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::ge_Tensor::call(self, other); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_2d_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..390c841110012ab2ac993e8131db088095d45929 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_2d_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 & grid_sampler_2d_out(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out); +TORCH_API at::Tensor grid_sampler_2d_cpu(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +TORCH_API at::Tensor grid_sampler_2d_cuda(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gru_cell_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gru_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4384a49b362c3a525b8421471dac1bf8626512a0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/gru_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 gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_hh={}); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/kl_div_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/kl_div_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4530aa9be8de9d56e49b171efb22185de877f525 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/kl_div_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 kl_div(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, bool log_target=false); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lift_fresh_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lift_fresh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2cad94381ed1bad9aab9ec46bcc52151de4d5bd7 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lift_fresh_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 lift_fresh { + 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::lift_fresh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lift_fresh(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e0d09b256eca126d36739274cbe7ab093d2655d6 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_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 linalg_cholesky(const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & linalg_cholesky_out(const at::Tensor & self, bool upper, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cond_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cond_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fd2bd54cad7476104a6b890e9dc8e9e7eec63400 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cond_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor linalg_cond(const at::Tensor & self, const ::std::optional & p=::std::nullopt); +TORCH_API at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p=::std::nullopt); +TORCH_API at::Tensor & linalg_cond_outf(const at::Tensor & self, const ::std::optional & p, at::Tensor & out); +TORCH_API at::Tensor linalg_cond(const at::Tensor & self, c10::string_view p); +TORCH_API at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, c10::string_view p); +TORCH_API at::Tensor & linalg_cond_outf(const at::Tensor & self, c10::string_view p, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lshift_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lshift_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e018b18ad2ab1d2aa9bd13148584a7304142df0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/lshift_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & __lshift___out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & __lshift___outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & __lshift___out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & __lshift___outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0da0108e932711216fc2381fb6433058ba00dc37 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_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 max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mean.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mean.h new file mode 100644 index 0000000000000000000000000000000000000000..c7ed0679d38c03ef35df127e7f4cc2cc4667ad78 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mean.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mean(Tensor self, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor mean(const at::Tensor & self, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean::call(self, dtype); +} + +// aten::mean.dtype_out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_dtype_out::call(self, dtype, out); +} +// aten::mean.dtype_out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_outf(const at::Tensor & self, ::std::optional dtype, at::Tensor & out) { + return at::_ops::mean_dtype_out::call(self, dtype, out); +} + +// aten::mean.dim(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_dim::call(self, dim, keepdim, dtype); +} + +// aten::mean.out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_out::call(self, dim, keepdim, dtype, out); +} +// aten::mean.out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::mean_out::call(self, dim, keepdim, dtype, out); +} + +// aten::mean.names_dim(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor mean(const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_names_dim::call(self, dim, keepdim, dtype); +} + +// aten::mean.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::mean_names_out::call(self, dim, keepdim, dtype, out); +} +// aten::mean.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mean_outf(const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::mean_names_out::call(self, dim, keepdim, dtype, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..f21fc13c068f16295ab8124ff15011861c196ca8 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu.h @@ -0,0 +1,47 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor miopen_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template ::value>> + at::Tensor miopen_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor miopen_convolution_add_relu_symint(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, stride, padding, dilation, groups); +} +namespace symint { + template ::value>> + at::Tensor miopen_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::miopen_convolution_add_relu::call(self, weight, z, alpha, bias, stride, padding, dilation, groups); + } +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..136b072202b9dee4cdaa81a718315450da7a236f --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_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 mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantile.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantile.h new file mode 100644 index 0000000000000000000000000000000000000000..bccbb49d97c330063ad5ef5d731331b0569b5f24 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantile.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor +inline at::Tensor quantile(const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::quantile::call(self, q, dim, keepdim, interpolation); +} + +// aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantile_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::quantile_out::call(self, q, dim, keepdim, interpolation, out); +} +// aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantile_outf(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { + return at::_ops::quantile_out::call(self, q, dim, keepdim, interpolation, out); +} + +// aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor +inline at::Tensor quantile(const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::quantile_scalar::call(self, q, dim, keepdim, interpolation); +} + +// aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantile_out(at::Tensor & out, const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::quantile_scalar_out::call(self, q, dim, keepdim, interpolation, out); +} +// aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantile_outf(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { + return at::_ops::quantile_scalar_out::call(self, q, dim, keepdim, interpolation, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_max_pool1d.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_max_pool1d.h new file mode 100644 index 0000000000000000000000000000000000000000..2affde5d2ed4b2cb40b235f8e52073d51a560ebc --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_max_pool1d.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::quantized_max_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor quantized_max_pool1d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::quantized_max_pool1d::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantized_max_pool1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::quantized_max_pool1d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantized_max_pool1d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { + return at::_ops::quantized_max_pool1d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/randint_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/randint_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e07d44afdb9faf66871d14a975e8d17b7b1bc0fa --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/randint_native.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & randint_out(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0fce1cb2483ef81ad59e4beb8e1a1575c3e640e5 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_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_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_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/softshrink_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..caebd9a5cee5115a09a8fc5da811f14d691f24c0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_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 softshrink(const at::Tensor & self, const at::Scalar & lambd=0.5); +TORCH_API at::Tensor & softshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5); +TORCH_API at::Tensor & softshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_csr_tensor.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_csr_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..9679a28c0289b35feee3c5c650af12660ce497cb --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_csr_tensor.h @@ -0,0 +1,43 @@ +#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::sparse_csr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_csr_tensor_crow_col_value_size::call(crow_indices, col_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_csr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_csr_tensor_crow_col_value_size::call(crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); +} + +// aten::sparse_csr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::TensorOptions options) { + return at::_ops::sparse_csr_tensor_crow_col_value::call(crow_indices, col_indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_csr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_csr_tensor_crow_col_value::call(crow_indices, col_indices, values, dtype, layout, device, pin_memory); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bf0a1f25b014f6d8ab0b65c7d3a47bda2eea1e14 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor sparse_resize_and_clear(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +TORCH_API const at::Tensor & sparse_resize_and_clear_out(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out); +TORCH_API const at::Tensor & sparse_resize_and_clear_(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1.h new file mode 100644 index 0000000000000000000000000000000000000000..2e91ac23269436c10a786070131843a75888539a --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1.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::special_bessel_j1(Tensor self) -> Tensor +inline at::Tensor special_bessel_j1(const at::Tensor & self) { + return at::_ops::special_bessel_j1::call(self); +} + +// aten::special_bessel_j1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_bessel_j1_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_bessel_j1_out::call(self, out); +} +// aten::special_bessel_j1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_bessel_j1_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_bessel_j1_out::call(self, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_compositeexplicitautogradnonfunctional_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e83ea950c7c808dcb3c9bf1261ed74bf9eac63a --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_chebyshev_polynomial_u(const at::Tensor & x, const at::Tensor & n); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_compositeimplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..678cac4a92cdbc8641b5293a52b11c4c4211c2ec --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_digamma(const at::Tensor & self); +TORCH_API at::Tensor & special_digamma_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_digamma_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0.h new file mode 100644 index 0000000000000000000000000000000000000000..69f19ca94354ce53c0c2ead1fee3f14f2986e539 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0.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::special_scaled_modified_bessel_k0(Tensor x) -> Tensor +inline at::Tensor special_scaled_modified_bessel_k0(const at::Tensor & x) { + return at::_ops::special_scaled_modified_bessel_k0::call(x); +} + +// aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_scaled_modified_bessel_k0_out(at::Tensor & out, const at::Tensor & x) { + return at::_ops::special_scaled_modified_bessel_k0_out::call(x, out); +} +// aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_scaled_modified_bessel_k0_outf(const at::Tensor & x, at::Tensor & out) { + return at::_ops::special_scaled_modified_bessel_k0_out::call(x, out); +} + +} diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cbc198c7a3b6ddc4972871569fedc01eee9ae1be --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k0_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_scaled_modified_bessel_k0 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_scaled_modified_bessel_k0") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_scaled_modified_bessel_k0(Tensor x) -> Tensor") + static at::Tensor call(const at::Tensor & x); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x); +}; + +struct TORCH_API special_scaled_modified_bessel_k0_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_scaled_modified_bessel_k0") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..08fb8e3d81af625a846cae37be570bcf7ef31470 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/split_with_sizes_copy_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 split_with_sizes_copy_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +TORCH_API void split_with_sizes_copy_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out); +TORCH_API void split_with_sizes_copy_symint_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0); +TORCH_API void split_with_sizes_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautogradnonfunctional_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..941b904eff3fcc72b50c30c7b82f2ff8e8f20dc6 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API ::std::vector split_with_sizes_copy(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +TORCH_API ::std::vector split_with_sizes_copy_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/swapaxes_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/swapaxes_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d9bb3420426cd54bfdfbf3abe9c3e73468e2386 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/swapaxes_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 swapaxes(const at::Tensor & self, int64_t axis0, int64_t axis1); +TORCH_API at::Tensor & swapaxes_(at::Tensor & self, int64_t axis0, int64_t axis1); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim_ops.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b699decb541c169e701309a6e837516ee3f65266 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim_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 take_along_dim_out { + using schema = at::Tensor & (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::take_along_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out); +}; + +struct TORCH_API take_along_dim { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::take_along_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..485a121dcbf04b8d22a7b1f977d5d38144408ecd --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional dim=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..32733249fff8d3385b3580105c14005bcf5378a4 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_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_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest3d_cpu_dispatch.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad33c175ef7602b0ee0cc94de6263fec63b1f0b9 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest3d_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_nearest3d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/values_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/values_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b829db4d1ab77b73faa710d4639d6f060f5ccc54 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/values_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor values_default(const at::Tensor & self); +TORCH_API at::Tensor values_nested(const at::Tensor & self); +TORCH_API at::Tensor values_sparse(const at::Tensor & self); +TORCH_API at::Tensor values_sparse_csr(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_like_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_like_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eb0d1cd08b388cc473cccf67e0bfc50f0eec0cb0 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_like_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 zeros_like(const at::Tensor & self, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & zeros_like_out(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_native.h b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ab1bad3edd461fc8406b92f3450c27aefe368b54 --- /dev/null +++ b/vllm/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @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 zeros(at::IntArrayRef size, ::std::optional names, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & zeros_names_out(at::IntArrayRef size, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor zeros_symint(c10::SymIntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & zeros_out(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & zeros_sparse_out(at::IntArrayRef size, at::Tensor & out); +} // namespace native +} // namespace at