FM / autograd

/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/autograd/

/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/autograd

Name	Size	Mode	Actions
functions/	-	0755	rm
generated/	-	0755	rm
utils/	-	0755	rm
anomaly_mode.h	1525	0644	edit dl rm
autograd.h	5294	0644	edit dl rm
autograd_not_implemented_fallback.h	201	0644	edit dl rm
cpp_hook.h	518	0644	edit dl rm
custom_function.h	14470	0644	edit dl rm
edge.h	1627	0644	edit dl rm
engine.h	17237	0644	edit dl rm
forward_grad.h	8583	0644	edit dl rm
function.h	25046	0644	edit dl rm
FunctionsManual.h	19904	0644	edit dl rm
function_hook.h	641	0644	edit dl rm
grad_mode.h	207	0644	edit dl rm
InferenceMode.h	182	0644	edit dl rm
input_buffer.h	1597	0644	edit dl rm
input_metadata.h	1384	0644	edit dl rm
profiler.h	112	0644	edit dl rm
profiler_kineto.h	9111	0644	edit dl rm
profiler_legacy.h	16930	0644	edit dl rm
profiler_utils.h	439	0644	edit dl rm
python_anomaly_mode.h	1246	0644	edit dl rm
python_autograd.h	388	0644	edit dl rm
python_cpp_function.h	2456	0644	edit dl rm
python_engine.h	1262	0644	edit dl rm
python_fft_functions.h	128	0644	edit dl rm
python_function.h	4099	0644	edit dl rm
python_hook.h	700	0644	edit dl rm
python_legacy_variable.h	299	0644	edit dl rm
python_linalg_functions.h	131	0644	edit dl rm
python_mode.h	425	0644	edit dl rm
python_nn_functions.h	127	0644	edit dl rm
python_saved_variable_hooks.h	883	0644	edit dl rm
python_special_functions.h	132	0644	edit dl rm
python_torch_functions.h	671	0644	edit dl rm
python_variable.h	1645	0644	edit dl rm
python_variable_indexing.h	313	0644	edit dl rm
record_function_ops.h	587	0644	edit dl rm
saved_variable.h	4322	0644	edit dl rm
saved_variable_hooks.h	272	0644	edit dl rm
symbolic.h	330	0644	edit dl rm
variable.h	33411	0644	edit dl rm
VariableTypeUtils.h	15086	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/autograd/input_buffer.h (1597B)

#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 <vector>
#include <utility>
#include <memory>
#include <ATen/ATen.h>

#include <torch/csrc/autograd/variable.h>
#include <c10/util/Optional.h>
#include <c10/core/Stream.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 torch::autograd

#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 #include #include #include #include #include #include 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& opt_producer_stream, const c10::optional& 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 variables(InputBuffer&& g); private: std::vector buffer; }; }} // namespace torch::autograd