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/saved_variable.h (4322B)

#pragma once

#include <torch/csrc/WindowsTorchApiMacro.h>
#include <torch/csrc/autograd/forward_grad.h>
#include <torch/csrc/autograd/saved_variable_hooks.h>

#include <ATen/ATen.h>

#include <cstdint>
#include <memory>

namespace torch { namespace autograd {

using Variable = at::Tensor;
struct Node;

TORCH_API extern const char* ERR_BACKWARD_TWICE;

/// A snapshot of a variable at a certain version. A `SavedVariable` stores
/// enough information to reconstruct a variable from a certain point in time.
class TORCH_API SavedVariable {
 public:
  SavedVariable() = default;
  SavedVariable(const Variable& variable, bool is_output, bool is_inplace_on_view=false);
  SavedVariable(const c10::optional<Variable>& variable, bool is_output, bool is_inplace_on_view=false);
  SavedVariable(SavedVariable&&) = default;
  SavedVariable& operator=(SavedVariable&&) = default;
  ~SavedVariable() {
    if (fw_grad_) {
      // See note [ Using ForwardGrad ]
      fw_grad_->clear();
    }
  }

/// Reconstructs the saved variable. Pass `saved_for` as the gradient
  /// function if constructing the `SavedVariable` with it would have caused a
  /// circular reference.
  Variable unpack(std::shared_ptr<Node> saved_for = nullptr) const;

void register_hooks(std::unique_ptr<SavedVariableHooks>&& hooks);

void reset_data();

private:
  // This field contains either:
  // 1. the variable to save
  // 2. or its tensor_data.
  // If storing the variable itself would create a circular reference,
  // we fall into the second case and its metadata is also saved separately.
  // In that case, the grad_fn must be passed in to the unpack function when
  // reconstructing the Variable (except when we are doing an inplace operation on
  // a view, see below).
  // The field saved_orignal_ below reflects the two cases: its value is true
  // in the first case and false in the second case.
  // The value data_.defined() can be false in three cases:
  // 1. SavedVariable was constructed without a Tensor (the value to save is None), in
  // that case was_default_constructed_ will be kept at true
  // 2. The saved variable has been released by calling SavedVariable::reset_data(), typically
  // during the backward pass
  // 3. Hooks have been registered. In that case, hooks_ will be defined instead.
  // Note that the value of saved_original_ only reflects what happened during the construction
  // of the SavedVariable. If saved_original_ is true, we saved the original tensor in data_,
  // but if the user registers hooks, we will no longer have it (despite the saved_original_ still
  // being true)
  at::Tensor data_;

// This field is used to store the forward AD gradients associated with
  // the saved Tensor. Note that this shared_ptr must never be shared with
  // either the saved Tensor or the unpacked Tensor. See note [ Using ForwardGrad ]
  std::shared_ptr<ForwardGrad> fw_grad_;

// Weak version of grad_fn_ that prevents leaks in rebase_history() for
  // inplace views.
  // This variable is used when the user chooses to create a SavedVariable with
  // is_inplace_on_view = true.
  // In that case, the grad_fn passed in to the unpack function at unwrapping
  // time is unused.
  std::weak_ptr<Node> weak_grad_fn_;
  c10::VariableVersion version_counter_;

uint32_t saved_version_ = 0;
  uint32_t output_nr_ = 0;
  bool was_default_constructed_ = true;
  bool is_inplace_on_view_ = false;
  bool saved_original_ = false;
  bool is_leaf_ = false;
  bool is_output_ = false;

// Hooks are a pair of functions pack_hook/unpack_hook that provides fine-grained control
  // over how the SavedVariable should save its data.
  // pack_hook is called upon registration, while unpack_hook is called when unpacking.
  std::unique_ptr<SavedVariableHooks> hooks_;
  // Fields grad_fn_, grad_accumulator_, and requires_grad_ are only used if hooks are defined.
  // They are set before pack_hook is called and used after unpack_hook is called.
  std::shared_ptr<Node> grad_fn_;
  std::weak_ptr<Node> grad_accumulator_;
  bool requires_grad_ = false;

void save_metadata(const Variable& data);
  static std::unique_ptr<SavedVariableHooks> get_default_hooks();
  void set_hooks_and_pack_data(std::unique_ptr<SavedVariableHooks>&& hooks, const Variable& data);
};
}} // namespace torch::autograd

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