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#pragma once
#include <torch/csrc/Export.h>
#include <memory>
#include <string>
namespace torch {
namespace autograd {
// forward declaration of Node from function.h
struct Node;
struct TORCH_API AnomalyMode {
static bool is_enabled() {
return _enabled;
}
static bool should_check_nan() {
return _check_nan;
}
static void set_enabled(bool enabled, bool check_nan = true) {
_enabled = enabled;
_check_nan = check_nan;
}
private:
static bool _enabled;
static bool _check_nan;
};
/// 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(bool check_nan = true);
~DetectAnomalyGuard();
private:
bool prev_check_nan_;
};
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_;
};
} // namespace autograd
} // namespace torch
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