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tf.keras.callbacks.Callback

Abstract base class used to build new callbacks.

Used in the notebooks

Used in the guide Used in the tutorials

Callbacks can be passed to keras methods such as fit, evaluate, and predict in order to hook into the various stages of the model training and inference lifecycle.

To create a custom callback, subclass keras.callbacks.Callback and override the method associated with the stage of interest. See https://www.tensorflow.org/guide/keras/custom_callback for more information.

Example:

training_finished = False
class MyCallback(tf.keras.callbacks.Callback):
  def on_train_end(self, logs=None):
    global training_finished
    training_finished = True
model = tf.keras.Sequential([tf.keras.layers.Dense(1, input_shape=(1,))])
model.compile(loss='mean_squared_error')
model.fit(tf.constant([[1.0]]), tf.constant([[1.0]]),
          callbacks=[MyCallback()])
assert training_finished == True

The logs dictionary that callback methods take as argument will contain keys for quantities relevant to the current batch or epoch (see method-specific docstrings).

params Dict. Training parameters (eg. verbosity, batch size, number of epochs...).
model Instance of keras.models.Model. Reference of the model being trained.

Methods

on_batch_begin

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A backwards compatibility alias for on_train_batch_begin.

on_batch_end

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A backwards compatibility alias for on_train_batch_end.

on_epoch_begin

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Called at the start of an epoch.

Subclasses should override for any actions to run. This function should only be called during TRAIN mode.

Args
epoch Integer, index of epoch.
logs Dict. Currently no data is passed to this argument for this method but that may change in the future.

on_epoch_end

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Called at the end of an epoch.

Subclasses should override for any actions to run. This function should only be called during TRAIN mode.

Args
epoch Integer, index of epoch.
logs Dict, metric results for this training epoch, and for the validation epoch if validation is performed. Validation result keys are prefixed with val_. For training epoch, the values of the Model's metrics are returned. Example : {'loss': 0.2, 'accuracy': 0.7}.

on_predict_batch_begin

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Called at the beginning of a batch in predict methods.

Subclasses should override for any actions to run.

Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.

Args
batch Integer, index of batch within the current epoch.
logs Dict, contains the return value of model.predict_step, it typically returns a dict with a key 'outputs' containing the model's outputs.

on_predict_batch_end