tf.keras.callbacks.Callback

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Abstract base class used to build new callbacks.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.callbacks.Callback

tf.keras.callbacks.Callback()

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).

Attributes
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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on_batch_begin(
    batch, logs=None
)

A backwards compatibility alias for on_train_batch_begin.

on_batch_end

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on_batch_end(
    batch, logs=None
)

A backwards compatibility alias for on_train_batch_end.

on_epoch_begin

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on_epoch_begin(
    epoch, logs=None
)

Called at the start of an epoch.

Subclasses should override for any actions to run. 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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on_epoch_end(
    epoch, logs=None
)

Called at the end of an epoch.

Subclasses should override for any actions to run. 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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on_predict_batch_begin(
    batch, logs=None
)

Called at the beginning of a batch in predict methods.

Subclasses should override for any actions to run.

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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on_predict_batch_end(
    batch, logs=None
)

Called at the end of a batch in predict methods.

Subclasses should override for any actions to run.

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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on_predict_begin(
    logs=None
)

Called at the beginning of prediction.

Subclasses should override for any actions to run.

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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on_predict_end(
    logs=None
)

Called at the end of prediction.

Subclasses should override for any actions to run.

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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on_test_batch_begin(
    batch, logs=None
)

Called at the beginning of a batch in evaluate methods.

Also called at the beginning of a validation batch in the fit methods, if validation data is provided.

Subclasses should override for any actions to run.

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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on_test_batch_end(
    batch, logs=None
)

Called at the end of a batch in evaluate methods.

Also called at the end of a validation batch in the fit methods, if validation data is provided.

Subclasses should override for any actions to run.

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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on_test_begin(
    logs=None
)

Called at the beginning of evaluation or validation.

Subclasses should override for any actions to run.

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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on_test_end(
    logs=None
)

Called at the end of evaluation or validation.

Subclasses should override for any actions to run.

Arguments
logs	Dict. Currently the output of the last call to on_test_batch_end() is passed to this argument for this method but that may change in the future.

on_train_batch_begin

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on_train_batch_begin(
    batch, logs=None
)

Called at the beginning of a training batch in fit methods.

Subclasses should override for any actions to run.

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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on_train_batch_end(
    batch, logs=None
)

Called at the end of a training batch in fit methods.

Subclasses should override for any actions to run.

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

on_train_begin

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on_train_begin(
    logs=None
)

Called at the beginning of training.

Subclasses should override for any actions to run.

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

on_train_end

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on_train_end(
    logs=None
)

Called at the end of training.

Subclasses should override for any actions to run.

Arguments
logs	Dict. Currently the output of the last call to on_epoch_end() is passed to this argument for this method but that may change in the future.

set_model

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set_model(
    model
)

set_params

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set_params(
    params
)