tf.keras.callbacks.CallbackList

Container abstracting a list of callbacks.

callbacks List of Callback instances.
add_history Whether a History callback should be added, if one does not already exist in the callbacks list.
add_progbar Whether a ProgbarLogger callback should be added, if one does not already exist in the callbacks list.
model The Model these callbacks are used with.
**params If provided, parameters will be passed to each Callback via Callback.set_params.

Methods

append

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on_batch_begin

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on_batch_end

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on_epoch_begin

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Calls the on_epoch_begin methods of its callbacks.

This function should only be called during TRAIN mode.

Arguments
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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Calls the on_epoch_end methods of its callbacks.

This function should only be called during TRAIN mode.

Arguments
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_.

on_predict_batch_begin

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Calls the on_predict_batch_begin methods of its callbacks.

Arguments
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

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Calls the on_predict_batch_end methods of its callbacks.

Arguments
batch Integer, index of batch within the current epoch.
logs Dict. Aggregated metric results up until this batch.

on_predict_begin

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Calls the 'on_predict_begin` methods of its callbacks.

Arguments
logs Dict. Currently no data is passed to this argument for this method but that may change in the future.

on_predict_end

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Calls the on_predict_end methods of its callbacks.

Arguments
logs Dict. Currently no data is passed to this argument for this method but that may change in the future.

on_test_batch_begin

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Calls the on_test_batch_begin methods of its callbacks.

Arguments
batch Integer, index of batch within the current epoch.
logs Dict, contains the return value of model.test_step. Typically, the values of the Model's metrics are returned. Example: {'loss': 0.2, 'accuracy': 0.7}.

on_test_batch_end

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Calls the on_test_batch_end methods of its callbacks.

Arguments
batch Integer, index of batch within the current epoch.
logs Dict. Aggregated metric results up until this batch.

on_test_begin

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Calls the on_test_begin methods of its callbacks.

Arguments
logs Dict. Currently no data is passed to this argument for this method but that may change in the future.

on_test_end

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Calls the on_test_end methods of its callbacks.

Arguments
logs Dict. Currently no data is passed to this argument for this method but that may change in the future.

on_train_batch_begin

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Calls the on_train_batch_begin methods of its callbacks.

Arguments
batch Integer, index of batch within the current epoch.
logs Dict, contains the return value of model.train_step. Typically, the values of the Model's metrics are returned. Example: {'loss': 0.2, 'accuracy': 0.7}.

on_train_batch_end

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Calls the on_train_bat