TFKerasPruningCallback#

class mergernet.model.callbacks.TFKerasPruningCallback[source]#

Bases: Callback

tf.keras callback to prune unpromising trials.

This callback is intend to be compatible for TensorFlow v1 and v2, but only tested with TensorFlow v2.

See the example if you want to add a pruning callback which observes the validation accuracy.

Parameters:

  • trial – A optuna.trial.Trial corresponding to the current evaluation of the objective function.

  • monitor – An evaluation metric for pruning, e.g., val_loss or val_acc.

_implements_predict_batch_hooks()#

Determines if this Callback should be called for each predict batch.

_implements_test_batch_hooks()#

Determines if this Callback should be called for each test batch.

_implements_train_batch_hooks()#

Determines if this Callback should be called for each train batch.

on_batch_begin(batch, logs=None)#

A backwards compatibility alias for on_train_batch_begin.

on_batch_end(batch, logs=None)#

A backwards compatibility alias for on_train_batch_end.

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.

Parameters:

  • 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(epoch: int, logs: Dict[str, Any] | None = None) → None[source]#

Called at the end of an epoch.

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

Parameters:

  • 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(batch, logs=None)#

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.

Parameters:

  • batch – Integer, index of batch within the current epoch.

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

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.

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.

Parameters:

  • batch – Integer, index of batch within the current epoch.

  • logs – Dict. Aggregated metric results up until this batch.

on_predict_begin(logs=None)#

Called at the beginning of prediction.

Subclasses should override for any actions to run.

Parameters:

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

on_predict_end(logs=None)#

Called at the end of prediction.

Subclasses should override for any actions to run.

Parameters:

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

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.

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.

Parameters:

  • batch – Integer, index of batch within the current epoch.

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

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.

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.

Parameters:

  • batch – Integer, index of batch within the current epoch.

  • logs – Dict. Aggregated metric results up until this batch.

on_test_begin(logs=None)#

Called at the beginning of evaluation or validation.

Subclasses should override for any actions to run.

Parameters:

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

on_test_end(logs=None)#

Called at the end of evaluation or validation.

Subclasses should override for any actions to run.

Parameters:

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(batch, logs=None)#

Called at the beginning of a training batch in fit 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.

Parameters:

  • batch – Integer, index of batch within the current epoch.

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

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.

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.

Parameters:

  • batch – Integer, index of batch within the current epoch.

  • logs – Dict. Aggregated metric results up until this batch.

on_train_begin(logs=None)#

Called at the beginning of training.

Subclasses should override for any actions to run.

Parameters:

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

on_train_end(logs=None)#

Called at the end of training.

Subclasses should override for any actions to run.

Parameters:

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(model)#
set_params(params)#
_keras_api_names = ('keras.callbacks.Callback',)#
_keras_api_names_v1 = ('keras.callbacks.Callback',)#