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/anomaly_mode.h (1525B)

#pragma once

#include <string>
#include <memory>
#include <torch/csrc/WindowsTorchApiMacro.h>

namespace torch { namespace autograd {

// forward declaration of Node from function.h
struct Node;

struct TORCH_API AnomalyMode {
  static bool is_enabled() {
    return _enabled;
  }
  static void set_enabled(bool enabled) {
    _enabled = enabled;
  }

private:
  static bool _enabled;
};

/// A RAII guard that enables Anomaly Detection Mode.
///
/// Anomaly detection mode is useful for debugging problems happening
/// in the backward, such as unexpectedly modified tensors or NaNs
/// occuring in the backward.
///
/// The enabling of anomaly mode is global - as soon as there is one
/// such guard, it is enabled for all computation and threads. It also
/// comes with a significant performance penalty.
///
/// Example:
/// @code
/// auto x = torch::tensor({1.}, torch::requires_grad());
/// {
///   torch::autograd::DetectAnomalyGuard detect_anomaly;
///   auto x = torch::tensor({5.0}, torch::requires_grad());
///   auto y = x * x;
///   auto z = y * y;
///   y += 1;
///   z.backward();
/// }
/// @endcode
class TORCH_API DetectAnomalyGuard {
 public:
  DetectAnomalyGuard();
  ~DetectAnomalyGuard();
};

struct TORCH_API AnomalyMetadata {
  virtual ~AnomalyMetadata();
  virtual void store_stack();
  virtual void print_stack(const std::string& current_node_name);
  virtual void assign_parent(const std::shared_ptr<Node>& parent_node);

private:
  std::string traceback_;
  std::shared_ptr<Node> parent_;
};

}}

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