|TensorFlow 2.0 version||View source on GitHub|
class BaseLogger: Callback that accumulates epoch averages of metrics.
class CSVLogger: Callback that streams epoch results to a csv file.
class Callback: Abstract base class used to build new callbacks.
class EarlyStopping: Stop training when a monitored quantity has stopped improving.
class History: Callback that records events into a
class LambdaCallback: Callback for creating simple, custom callbacks on-the-fly.
class LearningRateScheduler: Learning rate scheduler.
class ModelCheckpoint: Save the model after every epoch.
class ProgbarLogger: Callback that prints metrics to stdout.
class ReduceLROnPlateau: Reduce learning rate when a metric has stopped improving.
class RemoteMonitor: Callback used to stream events to a server.
class TensorBoard: Enable visualizations for TensorBoard.
class TerminateOnNaN: Callback that terminates training when a NaN loss is encountered.