diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d8ec93edd045a2e69319ea5586a1fb2eb0666710 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_addmm_activation.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_addmm_activation.h new file mode 100644 index 0000000000000000000000000000000000000000..60ecc85c8853f100fd8c9adb3d20c933e916b573 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_addmm_activation.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::_addmm_activation.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _addmm_activation_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1, bool use_gelu=false) { + return at::_ops::_addmm_activation_out::call(self, mat1, mat2, beta, alpha, use_gelu, out); +} +// aten::_addmm_activation.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _addmm_activation_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, bool use_gelu, at::Tensor & out) { + return at::_ops::_addmm_activation_out::call(self, mat1, mat2, beta, alpha, use_gelu, out); +} + +// aten::_addmm_activation(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False) -> Tensor +inline at::Tensor _addmm_activation(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1, bool use_gelu=false) { + return at::_ops::_addmm_activation::call(self, mat1, mat2, beta, alpha, use_gelu); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cummin_helper_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cummin_helper_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6ab7ca702be569796e14e231fe2252d155d1dad5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cummin_helper_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 void cummin_helper_cpu(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +TORCH_API void cummin_helper_cuda(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_dimV_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_dimV_native.h new file mode 100644 index 0000000000000000000000000000000000000000..db8e466385d18ce92fa451e91bee6d40958328e9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_dimV_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 int64_t dense_dim_sparse(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_efficient_attention_forward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_efficient_attention_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..5f495dcf303cc82dc302e4080894f57811d66939 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_efficient_attention_forward.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::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt? max_seqlen_q, SymInt? max_seqlen_k, float dropout_p, int custom_mask_type, bool compute_log_sumexp=False, *, float? scale=None, Tensor? seqlen_k=None, int? window_size=None) -> (Tensor output, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, SymInt max_seqlen_batch_q, SymInt max_seqlen_batch_k) +inline ::std::tuple _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_q)) : ::std::nullopt, max_seqlen_k.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_k)) : ::std::nullopt, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); +} +namespace symint { + template ::value>> + ::std::tuple _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_q)) : ::std::nullopt, max_seqlen_k.has_value() ? ::std::make_optional(c10::SymInt(*max_seqlen_k)) : ::std::nullopt, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); + } +} + +// aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt? max_seqlen_q, SymInt? max_seqlen_k, float dropout_p, int custom_mask_type, bool compute_log_sumexp=False, *, float? scale=None, Tensor? seqlen_k=None, int? window_size=None) -> (Tensor output, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, SymInt max_seqlen_batch_q, SymInt max_seqlen_batch_k) +inline ::std::tuple _efficient_attention_forward_symint(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); +} +namespace symint { + template ::value>> + ::std::tuple _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt) { + return at::_ops::_efficient_attention_forward::call(query, key, value, bias, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k, dropout_p, custom_mask_type, compute_log_sumexp, scale, seqlen_k, window_size); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10.h new file mode 100644 index 0000000000000000000000000000000000000000..234f6a87ee8d028fe6d1676533b11ec8c1d482c3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10.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::_foreach_log10(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log10(at::TensorList self) { + return at::_ops::_foreach_log10::call(self); +} + +// aten::_foreach_log10_(Tensor(a!)[] self) -> () +inline void _foreach_log10_(at::TensorList self) { + return at::_ops::_foreach_log10_::call(self); +} + +// aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log10_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log10_out::call(self, out); +} +// aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log10_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log10_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_adam_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_adam_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..323896bcf23f89d616ab8d66762eb62d8afaf7e6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_adam_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,::std::vector,::std::vector> _fused_adam(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adam_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adam_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adam(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adam_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adam_outf(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5e98cc3184bb7d4fa6da515a8513bd71ff6552d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _indices_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ee7ea5a01eb8336cbaf13750113e5ca765694922 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_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 ::std::tuple _linalg_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_values.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_values.h new file mode 100644 index 0000000000000000000000000000000000000000..7285bc318dbcc112e6f0ef61d5e722c9682dadcb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_values.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_nested_get_values(Tensor(a) self) -> Tensor(a) +inline at::Tensor _nested_get_values(const at::Tensor & self) { + return at::_ops::_nested_get_values::call(self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..24fe430ec34aa4bbc4f2a4a4dc9989fae34bf35a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _scaled_dot_product_efficient_attention { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, bool, double, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_scaled_dot_product_efficient_attention") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_scaled_dot_product_efficient_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, *, float? scale=None) -> (Tensor output, Tensor log_sumexp, Tensor philox_seed, Tensor philox_offset)") + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p, bool is_causal, ::std::optional scale); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p, bool is_causal, ::std::optional scale); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_shape_as_tensor.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_shape_as_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..f929928a47096606b5d0f9f78d0fe91520372508 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_shape_as_tensor.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::_shape_as_tensor(Tensor self) -> Tensor +inline at::Tensor _shape_as_tensor(const at::Tensor & self) { + return at::_ops::_shape_as_tensor::call(self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_unsafe_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_unsafe_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82b882f0adf5991786d5f1db82c9f8907a5d1167 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_unsafe_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 _sparse_coo_tensor_unsafe_symint(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=::std::nullopt); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f901a30fc1874fd5fcf17851fbc844fa630bb605 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_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 _test_autograd_multiple_dispatch_view { + 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::_test_autograd_multiple_dispatch_view") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch_view(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_functorch_fallback_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_functorch_fallback_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d29eaa40ecbaa4f85f507ca0734918a3f5917f09 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_functorch_fallback_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _test_functorch_fallback(const at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_optional_floatlist_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_optional_floatlist_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d1fa45e2a4ac9c5cf0915c866e9f84adfd520275 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_optional_floatlist_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 & _test_optional_floatlist_out(const at::Tensor & values, ::std::optional> addends, at::Tensor & out); +TORCH_API at::Tensor _test_optional_floatlist(const at::Tensor & values, ::std::optional> addends); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_optional_intlist.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_optional_intlist.h new file mode 100644 index 0000000000000000000000000000000000000000..770e369b971535cd0a82d4bc6bd5ff76da392dde --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_optional_intlist.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_test_optional_intlist(Tensor values, int[]? addends) -> Tensor +inline at::Tensor _test_optional_intlist(const at::Tensor & values, at::OptionalIntArrayRef addends) { + return at::_ops::_test_optional_intlist::call(values, addends); +} + +// aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_optional_intlist_out(at::Tensor & out, const at::Tensor & values, at::OptionalIntArrayRef addends) { + return at::_ops::_test_optional_intlist_out::call(values, addends, out); +} +// aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_optional_intlist_outf(const at::Tensor & values, at::OptionalIntArrayRef addends, at::Tensor & out) { + return at::_ops::_test_optional_intlist_out::call(values, addends, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e83ae863b90eba0ed17e59f5bc13a8881cf414e2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_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 _thnn_fused_gru_cell(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6e0b8deb59523cd7facf92383740ae9e9657314a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_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 _thnn_fused_gru_cell { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_thnn_fused_gru_cell") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_thnn_fused_gru_cell(Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias=None, Tensor? hidden_bias=None) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias); +}; + +struct TORCH_API _thnn_fused_gru_cell_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, 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::_thnn_fused_gru_cell") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_thnn_fused_gru_cell.out(Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias=None, Tensor? hidden_bias=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_bsc_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_bsc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7cfa4e0bb7c7b8ef8f190c2c9fa2e8b992bcbf3e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_bsc_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 _to_sparse_bsc { + using schema = at::Tensor (const at::Tensor &, 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::_to_sparse_bsc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim); +}; + +struct TORCH_API _to_sparse_bsc_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_to_sparse_bsc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..bbddbc9322e5f2be7bec8c26c76a001905b6e625 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); + } +} + +// aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_version_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_version_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b824d551c94d1a22bec0fa93f4178dcdaf72b55f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_version_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API int64_t _version(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_wrapped_quantized_linear_prepacked_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_wrapped_quantized_linear_prepacked_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d8048c8fbae68b8cf4c71d2ca22924370b33b912 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_wrapped_quantized_linear_prepacked_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 _wrapped_quantized_linear_prepacked { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_wrapped_quantized_linear_prepacked") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_wrapped_quantized_linear_prepacked(Tensor input, Tensor input_scale, Tensor input_zero_point, Tensor packed_weight, Tensor output_scale, Tensor output_zero_point, int out_channel) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & input_scale, const at::Tensor & input_zero_point, const at::Tensor & packed_weight, const at::Tensor & output_scale, const at::Tensor & output_zero_point, int64_t out_channel); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & input_scale, const at::Tensor & input_zero_point, const at::Tensor & packed_weight, const at::Tensor & output_scale, const at::Tensor & output_zero_point, int64_t out_channel); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b44a051c075db291286ad9e291f67ad7d092fc84 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple adaptive_max_pool3d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool3d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/any_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/any_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..de16dd8897a2eebbf5532d8acb9ae214b22370d0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/any_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor any(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/crow_indices_copy.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/crow_indices_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..85ae31472d3ac6db041c2fdb5d12ecd2fee02a0d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/crow_indices_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::crow_indices_copy(Tensor self) -> Tensor +inline at::Tensor crow_indices_copy(const at::Tensor & self) { + return at::_ops::crow_indices_copy::call(self); +} + +// aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & crow_indices_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::crow_indices_copy_out::call(self, out); +} +// aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & crow_indices_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::crow_indices_copy_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_grid_sampler.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_grid_sampler.h new file mode 100644 index 0000000000000000000000000000000000000000..9ce0fbaeb590571273b58c5772526c48af4d8b7d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_grid_sampler.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::cudnn_grid_sampler(Tensor self, Tensor grid) -> Tensor output +inline at::Tensor cudnn_grid_sampler(const at::Tensor & self, const at::Tensor & grid) { + return at::_ops::cudnn_grid_sampler::call(self, grid); +} + +// aten::cudnn_grid_sampler.out(Tensor self, Tensor grid, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_grid_sampler_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & grid) { + return at::_ops::cudnn_grid_sampler_out::call(self, grid, out); +} +// aten::cudnn_grid_sampler.out(Tensor self, Tensor grid, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_grid_sampler_outf(const at::Tensor & self, const at::Tensor & grid, at::Tensor & out) { + return at::_ops::cudnn_grid_sampler_out::call(self, grid, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/diag_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/diag_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..18eef869028c4ec0effcba10682a5b0aed7fd6cd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/diag_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 diag(const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & diag_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & diag_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/diagflat.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/diagflat.h new file mode 100644 index 0000000000000000000000000000000000000000..af156436eadaffe341033e0c173447a286c58df1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/diagflat.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::diagflat(Tensor self, int offset=0) -> Tensor +inline at::Tensor diagflat(const at::Tensor & self, int64_t offset=0) { + return at::_ops::diagflat::call(self, offset); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfinv_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfinv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3fd889fd414428b99f57b4d39a649bc6fc760e8c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfinv_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API erfinv { + 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::erfinv") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "erfinv(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 erfinv_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::erfinv_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "erfinv_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API erfinv_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::erfinv") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6b03e7111b705181620fb17378a8ebec5afebfcb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple fake_quantize_per_tensor_affine_cachemask_out(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple fake_quantize_per_tensor_affine_cachemask(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c671663364f991bde0b721a0d43ed4d3934910ee --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_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 fbgemm_linear_fp16_weight_fp32_activation { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fbgemm_linear_fp16_weight_fp32_activation") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fbgemm_linear_fp16_weight_fp32_activation(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/frac_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/frac_native.h new file mode 100644 index 0000000000000000000000000000000000000000..af00a64acc1589b90a7835c95907d03f977bb7fa --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/frac_native.h @@ -0,0 +1,29 @@ +#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_frac_out : public at::meta::structured_frac { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor frac_sparse(const at::Tensor & self); +TORCH_API at::Tensor & frac_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & frac_sparse_(at::Tensor & self); +TORCH_API at::Tensor frac_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & frac_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & frac_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geqrf.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geqrf.h new file mode 100644 index 0000000000000000000000000000000000000000..02f8de5df78dcaa3503bd36a7c1d7660f3722570 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geqrf.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::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) +inline ::std::tuple geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self) { + return at::_ops::geqrf_a::call(self, a, tau); +} +// aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) +inline ::std::tuple geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau) { + return at::_ops::geqrf_a::call(self, a, tau); +} + +// aten::geqrf(Tensor self) -> (Tensor a, Tensor tau) +inline ::std::tuple geqrf(const at::Tensor & self) { + return at::_ops::geqrf::call(self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/greater_equal_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/greater_equal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..001198a67530a3506e4f6cc2295c03abc598cd62 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/greater_equal_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_equal_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & greater_equal_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ff02f0756280681b89748b14df667fd501ff374 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1d367ba15c0d86c0bb167d175c0c987fe7473bdd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward.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::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::hardsigmoid_backward_grad_input::call(grad_output, self, grad_input); +} +// aten::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) { + return at::_ops::hardsigmoid_backward_grad_input::call(grad_output, self, grad_input); +} + +// aten::hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::hardsigmoid_backward::call(grad_output, self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..387902a87bbb0fc83e2e0eee66d98c9c3d7b11da --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_hardsigmoid_backward_out : public at::meta::structured_hardsigmoid_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/heaviside_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/heaviside_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..89834dee1d41873ba12d2cb18b059c006bf75b4e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/heaviside_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 heaviside(const at::Tensor & self, const at::Tensor & values); +TORCH_API at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values); +TORCH_API at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out); +TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hspmm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hspmm.h new file mode 100644 index 0000000000000000000000000000000000000000..4a0ab4554eecebec0d7f2f39c5305ca0e414b95c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hspmm.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::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hspmm_out(at::Tensor & out, const at::Tensor & mat1, const at::Tensor & mat2) { + return at::_ops::hspmm_out::call(mat1, mat2, out); +} +// aten::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hspmm_outf(const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::hspmm_out::call(mat1, mat2, out); +} + +// aten::hspmm(Tensor mat1, Tensor mat2) -> Tensor +inline at::Tensor hspmm(const at::Tensor & mat1, const at::Tensor & mat2) { + return at::_ops::hspmm::call(mat1, mat2); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_add_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_add_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fdbf44b7c04c0bac689bb16e864b8ffeefeed957 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_add_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor index_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & index_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a2ae14581517ba37e337fa89f41500694d221020 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_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 index(const at::Tensor & self, const c10::List<::std::optional> & indices); +TORCH_API at::Tensor & index_out(at::Tensor & out, const at::Tensor & self, const c10::List<::std::optional> & indices); +TORCH_API at::Tensor & index_outf(const at::Tensor & self, const c10::List<::std::optional> & indices, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/is_complex_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/is_complex_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cdf22795b74ea5f92f7e7537359496892c31350d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/is_complex_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 is_complex { + using schema = bool (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::is_complex") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "is_complex(Tensor self) -> bool") + static bool call(const at::Tensor & self); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lcm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lcm.h new file mode 100644 index 0000000000000000000000000000000000000000..c7e22676150947b23081c796aa2ad1cee2b457b3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lcm.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::lcm.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lcm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::lcm_out::call(self, other, out); +} +// aten::lcm.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & lcm_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::lcm_out::call(self, other, out); +} + +// aten::lcm(Tensor self, Tensor other) -> Tensor +inline at::Tensor lcm(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::lcm::call(self, other); +} + +// aten::lcm_(Tensor(a!) self, Tensor other) -> Tensor(a!) +inline at::Tensor & lcm_(at::Tensor & self, const at::Tensor & other) { + return at::_ops::lcm_::call(self, other); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross.h new file mode 100644 index 0000000000000000000000000000000000000000..8d8ab4348a5652cb7b09a97235ef9dc3ef839e1c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross.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::linalg_cross(Tensor self, Tensor other, *, int dim=-1) -> Tensor +inline at::Tensor linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1) { + return at::_ops::linalg_cross::call(self, other, dim); +} + +// aten::linalg_cross.out(Tensor self, Tensor other, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, int64_t dim=-1) { + return at::_ops::linalg_cross_out::call(self, other, dim, out); +} +// aten::linalg_cross.out(Tensor self, Tensor other, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cross_outf(const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out) { + return at::_ops::linalg_cross_out::call(self, other, dim, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals.h new file mode 100644 index 0000000000000000000000000000000000000000..c6b1b170f81e9ec522b917ff40ba0fcdac569a58 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals.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::linalg_eigvals(Tensor self) -> Tensor +inline at::Tensor linalg_eigvals(const at::Tensor & self) { + return at::_ops::linalg_eigvals::call(self); +} + +// aten::linalg_eigvals.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_eigvals_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::linalg_eigvals_out::call(self, out); +} +// aten::linalg_eigvals.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_eigvals_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::linalg_eigvals_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex.h new file mode 100644 index 0000000000000000000000000000000000000000..eda13288124d4044df90bab5a462ffcb1174dcba --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex.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::linalg_lu_factor_ex(Tensor A, *, bool pivot=True, bool check_errors=False) -> (Tensor LU, Tensor pivots, Tensor info) +inline ::std::tuple linalg_lu_factor_ex(const at::Tensor & A, bool pivot=true, bool check_errors=false) { + return at::_ops::linalg_lu_factor_ex::call(A, pivot, check_errors); +} + +// aten::linalg_lu_factor_ex.out(Tensor A, *, bool pivot=True, bool check_errors=False, Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) +inline ::std::tuple linalg_lu_factor_ex_out(at::Tensor & LU, at::Tensor & pivots, at::Tensor & info, const at::Tensor & A, bool pivot=true, bool check_errors=false) { + return at::_ops::linalg_lu_factor_ex_out::call(A, pivot, check_errors, LU, pivots, info); +} +// aten::linalg_lu_factor_ex.out(Tensor A, *, bool pivot=True, bool check_errors=False, Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LU, Tensor(b!) pivots, Tensor(c!) info) +inline ::std::tuple linalg_lu_factor_ex_outf(const at::Tensor & A, bool pivot, bool check_errors, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info) { + return at::_ops::linalg_lu_factor_ex_out::call(A, pivot, check_errors, LU, pivots, info); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool1d_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool1d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ee83af7db0996e8fea9dd3db1807496bda078dc7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool1d_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_pool1d(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/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8f84c90f467598bb4a2162d8d0bfcb40d5450c49 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API max_pool2d_with_indices_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, 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::max_pool2d_with_indices_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input); +}; + +struct TORCH_API max_pool2d_with_indices_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, 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::max_pool2d_with_indices_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_pool2d_with_indices_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_rnn_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_rnn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4f9f9ed1a67ed08a6a14dd2180ba72562c580c98 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_rnn_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple miopen_rnn_out(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +TORCH_API ::std::tuple miopen_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..99494775bfb89973642b2a4d8934658baf35ebee --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mkldnn_linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); +TORCH_API ::std::tuple mkldnn_linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nextafter_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nextafter_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c320c412a3566746310eaa57d4f8ef4ec42fa43 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nextafter_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 nextafter(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & nextafter_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/norm_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..233ec87b1ce1ffcdb19ab5d324dfa556304ca343 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/norm_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 norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ba69e90ecf528054d2f712d37f16dccfafd02cb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_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 & 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); +TORCH_API 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); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8ffab7d04ec2992d24b7420e5b242b94a520833c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_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 quantized_max_pool1d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantized_max_pool1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "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") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API quantized_max_pool1d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantized_max_pool1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "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!)") + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randperm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randperm.h new file mode 100644 index 0000000000000000000000000000000000000000..7063171f054ac0e208836d189e542eb76fbd1f6f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randperm.h @@ -0,0 +1,201 @@ +#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::randperm(SymInt n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm(int64_t n, at::TensorOptions options=at::kLong) { + return at::_ops::randperm::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor randperm(int64_t n, at::TensorOptions options=at::kLong) { + return at::_ops::randperm::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randperm(SymInt n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm(int64_t n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm::call(n, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor randperm(int64_t n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm::call(n, dtype, layout, device, pin_memory); + } +} + +// aten::randperm(SymInt n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm_symint(c10::SymInt n, at::TensorOptions options=at::kLong) { + return at::_ops::randperm::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor randperm(c10::SymInt n, at::TensorOptions options=at::kLong) { + return at::_ops::randperm::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randperm(SymInt n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm_symint(c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm::call(n, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor randperm(c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm::call(n, dtype, layout, device, pin_memory); + } +} + +// aten::randperm.generator(SymInt n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm(int64_t n, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randperm_generator::call(n, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor randperm(int64_t n, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randperm_generator::call(n, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randperm.generator(SymInt n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm(int64_t n, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm_generator::call(n, generator, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor randperm(int64_t n, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm_generator::call(n, generator, dtype, layout, device, pin_memory); + } +} + +// aten::randperm.generator(SymInt n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm_symint(c10::SymInt n, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randperm_generator::call(n, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor randperm(c10::SymInt n, ::std::optional generator, at::TensorOptions options=at::kLong) { + return at::_ops::randperm_generator::call(n, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randperm.generator(SymInt n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randperm_symint(c10::SymInt n, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm_generator::call(n, generator, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor randperm(c10::SymInt n, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randperm_generator::call(n, generator, dtype, layout, device, pin_memory); + } +} + +// aten::randperm.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_out(at::Tensor & out, int64_t n) { + return at::_ops::randperm_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_out(at::Tensor & out, int64_t n) { + return at::_ops::randperm_out::call(n, out); + } +} + +// aten::randperm.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_outf(int64_t n, at::Tensor & out) { + return at::_ops::randperm_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_outf(int64_t n, at::Tensor & out) { + return at::_ops::randperm_out::call(n, out); + } +} + +// aten::randperm.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_symint_out(at::Tensor & out, c10::SymInt n) { + return at::_ops::randperm_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_out(at::Tensor & out, c10::SymInt n) { + return at::_ops::randperm_out::call(n, out); + } +} + +// aten::randperm.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_symint_outf(c10::SymInt n, at::Tensor & out) { + return at::_ops::randperm_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_outf(c10::SymInt n, at::Tensor & out) { + return at::_ops::randperm_out::call(n, out); + } +} + +// aten::randperm.generator_out(SymInt n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_out(at::Tensor & out, int64_t n, ::std::optional generator) { + return at::_ops::randperm_generator_out::call(n, generator, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_out(at::Tensor & out, int64_t n, ::std::optional generator) { + return at::_ops::randperm_generator_out::call(n, generator, out); + } +} + +// aten::randperm.generator_out(SymInt n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_outf(int64_t n, ::std::optional generator, at::Tensor & out) { + return at::_ops::randperm_generator_out::call(n, generator, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_outf(int64_t n, ::std::optional generator, at::Tensor & out) { + return at::_ops::randperm_generator_out::call(n, generator, out); + } +} + +// aten::randperm.generator_out(SymInt n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_symint_out(at::Tensor & out, c10::SymInt n, ::std::optional generator) { + return at::_ops::randperm_generator_out::call(n, generator, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_out(at::Tensor & out, c10::SymInt n, ::std::optional generator) { + return at::_ops::randperm_generator_out::call(n, generator, out); + } +} + +// aten::randperm.generator_out(SymInt n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randperm_symint_outf(c10::SymInt n, ::std::optional generator, at::Tensor & out) { + return at::_ops::randperm_generator_out::call(n, generator, out); +} +namespace symint { + template ::value>> + at::Tensor & randperm_outf(c10::SymInt n, ::std::optional generator, at::Tensor & out) { + return at::_ops::randperm_generator_out::call(n, generator, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b79f15be13172a8f59ddd505115fa1cafdf49339 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d_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 at::Tensor reflection_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/remainder_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/remainder_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d29a4bee8b4d293a1d8a6840694f3acb3368c4d1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/remainder_cuda_dispatch.h @@ -0,0 +1,27 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 remainder(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & remainder_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor remainder(const at::Scalar & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/round_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/round_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd43946208ce0e60a09444ea4bb78c4b3ccb21dc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/round_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor round(const at::Tensor & self); +TORCH_API at::Tensor & round_(at::Tensor & self); +TORCH_API at::Tensor round(const at::Tensor & self, int64_t decimals); +TORCH_API at::Tensor & round_(at::Tensor & self, int64_t decimals); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e93ccf0367d83c3eeae71196b1fa051992eba8da --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sign { + 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::sign") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sign(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 sign_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sign_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sign_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API sign_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::sign") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sign.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..411e0505aee45a1e3c306f70700c58e82a55e0c2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor slow_conv_transpose2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_transpose2d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor & slow_conv_transpose2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor & slow_conv_transpose2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cd57d81c6ab0aaef3105a006cfb8d6ddf35c8ecd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_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_special_chebyshev_polynomial_v : public TensorIteratorBase { + + + void meta(const at::Tensor & x, const at::Tensor & n); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_erfinv_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_erfinv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2b949ff4e12fb1d5deaf4a0b8960744714bd8d05 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_erfinv_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 special_erfinv(const at::Tensor & self); +TORCH_API at::Tensor & special_erfinv_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_expit_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_expit_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a4be0141f3a2594547c4ad9817a921e650819985 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_expit_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_expit(const at::Tensor & self); +TORCH_API at::Tensor & special_expit_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_expit_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/stack_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/stack_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b04702351bdc36b44d86d3e78d6a2e25fb9c44f6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/stack_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 stack(at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & stack_out(at::TensorList tensors, int64_t dim, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/svd_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/svd_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f92a4b7fd10eb9a9f85f9ba0f55dddb0831fe436 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/svd_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 svd_U { + using schema = ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::svd") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "U") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V)") + static ::std::tuple call(const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V); +}; + +struct TORCH_API svd { + using schema = ::std::tuple (const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::svd") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "svd(Tensor self, bool some=True, bool compute_uv=True) -> (Tensor U, Tensor S, Tensor V)") + static ::std::tuple call(const at::Tensor & self, bool some, bool compute_uv); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool some, bool compute_uv); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_constrain_range.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_constrain_range.h new file mode 100644 index 0000000000000000000000000000000000000000..0c89bea227cb953521a6a295976cd6e50dd723f1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_constrain_range.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sym_constrain_range(Scalar size, *, int? min=None, int? max=None) -> () +inline void sym_constrain_range(const at::Scalar & size, ::std::optional min=::std::nullopt, ::std::optional max=::std::nullopt) { + return at::_ops::sym_constrain_range::call(size, min, max); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44634d72c4541d512729ac492766758ccfc3c657 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_size_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 c10::SymInt sym_size(const at::Tensor & self, int64_t dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_backward_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..73b0386d74677a2ac9e33e880a00de6fdd8d786d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_backward_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 threshold_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +TORCH_API at::Tensor & threshold_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +TORCH_API at::Tensor & threshold_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/tril_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/tril_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1b9e1fe036a0b8c9e09aa1050bf4c192cb9c7742 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/tril_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 tril(const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); +TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold.h new file mode 100644 index 0000000000000000000000000000000000000000..f139e8d0ef08640c1ab2e3c9a475b7c3c2731eec --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold.h @@ -0,0 +1,26 @@ +#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 { + + + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..83b8cc4e62b2f1f40aa4004d123027ae1222bdfc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a7cfb3fe4ab165242a91b9448bc5501c60ef45b2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_linear1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & upsample_linear1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_real_copy_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_real_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..86d644a2f214ba08720dcc0b946e9044ed2e7bd9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_real_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor view_as_real_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/xlogy_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/xlogy_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9010f9c905d49bf2d3438b5968b1a0db8b7db231 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/xlogy_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 xlogy(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & xlogy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & xlogy_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & xlogy_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at