tfa.callbacks.AverageModelCheckpoint

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The callback that should be used with optimizers that extend

Used in the notebooks

Used in the tutorials

AverageWrapper, i.e., MovingAverage and StochasticAverage optimizers. It saves and, optionally, assigns the averaged weights.

update_weights If True, assign the moving average weights to the model, and save them. If False, keep the old non-averaged weights, but the saved model uses the average weights.

See tf.keras.callbacks.ModelCheckpoint for the other args.

Methods

set_model

View source

set_params