deephyper.contrib.callbacks.stop_on_timeout.TerminateOnTimeOut

deephyper.contrib.callbacks.stop_on_timeout.TerminateOnTimeOut

class deephyper.contrib.callbacks.stop_on_timeout.TerminateOnTimeOut(timeout_in_min=10)[source]

Bases: keras.callbacks.Callback

Methods

on_batch_begin

A backwards compatibility alias for on_train_batch_begin.

on_batch_end

A backwards compatibility alias for on_train_batch_end.

on_epoch_begin

Called at the start of an epoch.

on_epoch_end

Called at the end of an epoch.

on_predict_batch_begin

Called at the beginning of a batch in predict methods.

on_predict_batch_end

Called at the end of a batch in predict methods.

on_predict_begin

Called at the beginning of prediction.

on_predict_end

Called at the end of prediction.

on_test_batch_begin

Called at the beginning of a batch in evaluate methods.

on_test_batch_end

Called at the end of a batch in evaluate methods.

on_test_begin

Called at the beginning of evaluation or validation.

on_test_end

Called at the end of evaluation or validation.

on_train_batch_begin

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

on_train_batch_end

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

on_train_begin

Called at the beginning of training.

on_train_end

Called at the end of training.

set_model

set_params

on_batch_begin(batch, logs=None)

A backwards compatibility alias for on_train_batch_begin.

on_batch_end(epoch, logs={})[source]

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, 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.

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={})[source]

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.