Callbacks: utilities called at certain points during model training.
Classes
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 aHistoryobject.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.
