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► Keras 3 API documentation / Callbacks API / TerminateOnNaN

TerminateOnNaN

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TerminateOnNaN class

keras.callbacks.TerminateOnNaN(raise_error: bool = False)

Callback that terminates training when a NaN loss is encountered.

This callback monitors the loss value during training and terminates training when a NaN or Inf loss is detected. By default, training is stopped gracefully by setting model.stop_training = True, which triggers all callback cleanup methods including on_train_end().

Alternatively, you can use raise_error=True to immediately raise a RuntimeError when NaN/Inf is detected. This raise_error termination prevents on_train_end() from being called on other callbacks, which is useful for preserving backup states or preventing unintended cleanup when training fails.

Arguments

  • raise_error: Boolean, default False. If False, uses graceful stop via model.stop_training = True. If True, immediately raises RuntimeError on NaN/Inf loss, bypassing callback cleanup methods.

Example

# Graceful termination (default)
callback = keras.callbacks.TerminateOnNaN()
model.fit(x, y, callbacks=[callback])

# raise_error termination (strict failure)
callback = keras.callbacks.TerminateOnNaN(raise_error=True)
model.fit(x, y, callbacks=[callback])
TerminateOnNaN
TerminateOnNaN class