#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 kaiser_window(int64_t window_length, at::TensorOptions options={}); TORCH_API at::Tensor kaiser_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); TORCH_API at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length); TORCH_API at::Tensor & kaiser_window_outf(int64_t window_length, at::Tensor & out); TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, at::TensorOptions options={}); TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); TORCH_API at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length, bool periodic); TORCH_API at::Tensor & kaiser_window_outf(int64_t window_length, bool periodic, at::Tensor & out); TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, at::TensorOptions options={}); TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); TORCH_API at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length, bool periodic, double beta); TORCH_API at::Tensor & kaiser_window_outf(int64_t window_length, bool periodic, double beta, at::Tensor & out); } // namespace compositeexplicitautograd } // namespace at