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))