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