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#pragma once
// The InputBuffer class accumulates a list of Variables for use by a
// function. It implements logic to avoid modifying the passed
// values in-place (adding an input twice will accumulate the result).
// This behaviour is needed and used only in backward graphs.
#include <memory>
#include <utility>
#include <vector>
#include <c10/core/Stream.h>
#include <c10/util/Optional.h>
#include <torch/csrc/autograd/variable.h>
namespace torch {
namespace autograd {
struct InputBuffer {
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
explicit InputBuffer(size_t size) : buffer(size) {}
InputBuffer(const InputBuffer& other) = delete;
InputBuffer(InputBuffer&& other) = default;
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
explicit InputBuffer(variable_list&& inputs) : buffer(std::move(inputs)){};
InputBuffer& operator=(InputBuffer&& other) = default;
// Accumulates the variable at a specified index.
// The optional CUDA streams determine which stream the accumulation
// is run on and how the addition is synchronized.
void add(
size_t pos,
Variable&& var,
const c10::optional<c10::Stream>& opt_producer_stream,
const c10::optional<c10::Stream>& opt_consumer_stream);
at::Device device() const;
Variable operator[](size_t pos) {
return buffer[pos];
}
// Returns the inputs as a list of variables. Destroys given InputBuffer.
static std::vector<Variable> variables(InputBuffer&& g);
private:
std::vector<Variable> buffer;
};
} // namespace autograd
} // namespace torch
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