contrib.keras.callbacks.Callback

tf.contrib.keras.callbacks.Callback

class tf.contrib.keras.callbacks.Callback

Defined in tensorflow/contrib/keras/python/keras/callbacks.py.

Abstract base class used to build new callbacks.

Properties

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.

Currently, the .fit() method of the Sequential model class will include the following quantities in the logs that it passes to its callbacks:

on_epoch_end: logs include `acc` and `loss`, and
    optionally include `val_loss`
    (if validation is enabled in `fit`), and `val_acc`
    (if validation and accuracy monitoring are enabled).
on_batch_begin: logs include `size`,
    the number of samples in the current batch.
on_batch_end: logs include `loss`, and optionally `acc`
    (if accuracy monitoring is enabled).

Methods

__init__

__init__()

on_batch_begin

on_batch_begin(
    batch,
    logs=None
)

on_batch_end

on_batch_end(
    batch,
    logs=None
)

on_epoch_begin

on_epoch_begin(
    epoch,
    logs=None
)

on_epoch_end

on_epoch_end(
    epoch,
    logs=None
)

on_train_begin

on_train_begin(logs=None)

on_train_end

on_train_end(logs=None)

set_model

set_model(model)

set_params

set_params(params)