mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
1f3ff5ced2
* Miscellaneous documentation around autograd. Signed-off-by: Edward Z. Yang <ezyang@fb.com>
38 lines
1.2 KiB
C++
38 lines
1.2 KiB
C++
#pragma once
|
|
|
|
#include <functional>
|
|
#include <memory>
|
|
#include <array>
|
|
|
|
#include "torch/csrc/autograd/function.h"
|
|
#include "torch/csrc/autograd/variable.h"
|
|
|
|
namespace torch { namespace autograd {
|
|
|
|
using function_constructor = std::function<std::shared_ptr<Function>(FunctionFlags)>;
|
|
|
|
template<typename ...Args>
|
|
inline variable_list as_variable_list(Args&& ... args) {
|
|
std::array<variable_list::value_type, sizeof...(args)> arr = { {std::move(args)...} };
|
|
return variable_list(std::make_move_iterator(arr.begin()),
|
|
std::make_move_iterator(arr.end()));
|
|
}
|
|
|
|
template<typename ...Args>
|
|
inline tensor_list as_tensor_list(Args&& ... args) {
|
|
std::array<tensor_list::value_type, sizeof...(args)> arr = { {std::move(args)...} };
|
|
return tensor_list(std::make_move_iterator(arr.begin()),
|
|
std::make_move_iterator(arr.end()));
|
|
}
|
|
|
|
|
|
/**
|
|
* Wraps the tensor outputs in variables, and if necessary (i.e., none of the
|
|
* inputs are volatile), uses the function ctr and inputs to create a grad_fn
|
|
* for each of them.
|
|
*/
|
|
variable_list wrap_outputs(const variable_list& inputs, tensor_list&& outputs,
|
|
function_constructor ctr);
|
|
|
|
}}
|