5 分钟读懂Python 中的 Hook 钩子函数

　　@keras_export('keras.callbacks.Callback')

　　class Callback(object):

　　"""Abstract base class used to build new callbacks.

　　Attributes:

　　params: Dict. Training parameters

　　(eg. verbosity, batch size, number of epochs...).

　　model: Instance of `keras.models.Model`.

　　Reference of the model being trained.

　　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).

　　"""

　　def __init__(self):

　　self.validation_data = None # pylint: disable=g-missing-from-attributes

　　self.model = None

　　# Whether this Callback should only run on the chief worker in a

　　# Multi-Worker setting.

　　# TODO(omalleyt): Make this attr public once solution is stable.

　　self._chief_worker_only = None

　　self._supports_tf_logs = False

　　def set_params(self, params):

　　self.params = params

　　def set_model(self, model):

　　self.model = model

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_batch_begin(self, batch, logs=None):

　　"""A backwards compatibility alias for `on_train_batch_begin`."""

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_batch_end(self, batch, logs=None):

　　"""A backwards compatibility alias for `on_train_batch_end`."""

　　@doc_controls.for_subclass_implementers

　　def on_epoch_begin(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_epoch_end(self, 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_`.

　　"""

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_train_batch_begin(self, 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}`.

　　"""

　　# For backwards compatibility.

　　self.on_batch_begin(batch, logs=logs)

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_train_batch_end(self, 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.

　　"""

　　# For backwards compatibility.

　　self.on_batch_end(batch, logs=logs)

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_test_batch_begin(self, 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}`.

　　"""

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_test_batch_end(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_predict_batch_begin(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　@generic_utils.default

　　def on_predict_batch_end(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_train_begin(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_train_end(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_test_begin(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_test_end(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_predict_begin(self, 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.

　　"""

　　@doc_controls.for_subclass_implementers

　　def on_predict_end(self, 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.

　　"""

　　def _implements_train_batch_hooks(self):

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

　　return (not generic_utils.is_default(self.on_batch_begin) or

　　not generic_utils.is_default(self.on_batch_end) or

　　not generic_utils.is_default(self.on_train_batch_begin) or

　　not generic_utils.is_default(self.on_train_batch_end))