def _fit_distributed(self, dataset, epochs, **kwargs):
self.tf_optimizer = TFOptimizer.from_keras(self.model,
dataset,
model_dir=self.model_dir,
**kwargs)
self.tf_optimizer.optimize(MaxEpoch(epochs))
def _fit_distributed(self, dataset, validation_split, epochs, **kwargs):
self.tf_optimizer = TFOptimizer.from_keras(self.model, dataset,
val_split=validation_split, **kwargs)
if self.train_summary is not None:
self.tf_optimizer.set_train_summary(self.train_summary)
if self.val_summary is not None:
self.tf_optimizer.set_val_summary(self.val_summary)
self.tf_optimizer.optimize(MaxEpoch(epochs))
