#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 rand(at::IntArrayRef size, c10::optional names, at::TensorOptions options={}); TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional names, at::TensorOptions options={}); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, c10::optional names); TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, c10::optional names, at::Tensor & out); TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional names); TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, c10::optional names, at::Tensor & out); TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, c10::optional names, at::TensorOptions options={}); TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::TensorOptions options={}); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, c10::optional generator, c10::optional names); TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional generator, c10::optional names); TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); TORCH_API at::Tensor rand(at::IntArrayRef size, at::TensorOptions options={}); TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size); TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, at::Tensor & out); TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size); TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, at::Tensor & out); TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, at::TensorOptions options={}); TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, at::TensorOptions options={}); TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); } // namespace compositeexplicitautograd } // namespace at