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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 <utility>
#include <vector>
#include <c10/core/Stream.h>
#include <torch/csrc/autograd/variable.h>
#include <optional>
namespace torch::autograd {
struct InputBuffer {
explicit InputBuffer(size_t size) : buffer(size) {}
InputBuffer(const InputBuffer& other) = delete;
InputBuffer(InputBuffer&& other) = default;
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.
TORCH_API void add(
size_t pos,
Variable&& var,
const std::optional<c10::Stream>& opt_producer_stream,
const std::optional<c10::Stream>& opt_consumer_stream);
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);
std::vector<Variable> buffer;
};
} // namespace torch::autograd
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