Source code for pytorch_lightning.utilities.finite_checks
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"""Helper functions to detect NaN/Inf values."""
import logging
import torch
import torch.nn as nn
log = logging.getLogger(__name__)
[docs]def print_nan_gradients(model: nn.Module) -> None:
"""Iterates over model parameters and prints out parameter + gradient information if NaN."""
for param in model.parameters():
if (param.grad is not None) and torch.isnan(param.grad.float()).any():
log.info(f"{param}, {param.grad}")
[docs]def detect_nan_parameters(model: nn.Module) -> None:
"""Iterates over model parameters and prints gradients if any parameter is not finite.
Raises:
ValueError:
If ``NaN`` or ``inf`` values are found
"""
for name, param in model.named_parameters():
if not torch.isfinite(param).all():
print_nan_gradients(model)
raise ValueError(
f"Detected nan and/or inf values in `{name}`."
" Check your forward pass for numerically unstable operations."
)