tfa.callbacks.AverageModelCheckpoint
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The callback that saves average model weights.
tfa.callbacks.AverageModelCheckpoint(
update_weights: bool,
filepath: str,
monitor: str = 'val_loss',
verbose: int = 0,
save_best_only: bool = False,
save_weights_only: bool = False,
mode: str = 'auto',
save_freq: str = 'epoch',
**kwargs
)
Used in the notebooks
| Used in the tutorials |
|---|
The callback that should be used with optimizers that extend
tfa.optimizers.AveragedOptimizerWrapper, i.e.,
tfa.optimizers.MovingAverage and
tfa.optimizers.StochasticAverage optimizers.
It saves and, optionally, assigns the averaged weights.
Args | |
|---|---|
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 |
Methods
set_model
set_model(
model
)
set_params
set_params(
params
)