1657df9da12fe0861fa3d1e53e5b59cc57f73973,nussl/deep/train/trainer.py,Trainer,fit,#Trainer#,242

Before Change

                else lowest_validation_loss
            )

            self.progress_bar.update(1)
            self.progress_bar.set_description(f"Loss: {epoch_loss["loss"]:.4f}")


    def validate(self, key) -> float:

After Change

        fit_start_time = time.time()

        for self.num_epoch in range(self.num_epoch, self.options["num_epochs"]):
            start_time = time.time()
            epoch_loss = self.run_epoch("training")
            self.log_to_tensorboard(epoch_loss, self.num_epoch, "epoch")
            validation_loss = self.validate("validation")
            self.save(validation_loss["loss"] < lowest_validation_loss)
            lowest_validation_loss = (
                validation_loss["loss"] 
                if validation_loss["loss"] < lowest_validation_loss
                else lowest_validation_loss
            )

            epoch_elapsed_time = time.time() - start_time
            epoch_elapsed_time = time.strftime("%H:%M:%S", time.gmtime(epoch_elapsed_time))
            full_elapsed_time = time.time() - fit_start_time
            full_elapsed_time = time.strftime("%H:%M:%S", time.gmtime(full_elapsed_time))

Instances