102123eef25500a39160412eca7e8cb9f53104a6,trainer/trainer.py,Trainer,_valid_epoch,#Trainer#Any#,94

Before Change

        return {
            "val_loss": total_val_loss / len(self.valid_data_loader),
            "val_metrics": (total_val_metrics / len(self.valid_data_loader)).tolist()
        }

    def _progress(self, batch_idx):
        base = "[{}/{} ({:.0f}%)]"

After Change

                self.writer.set_step((epoch - 1) * len(self.valid_data_loader) + batch_idx, "valid")
                self.valid_metrics.update("loss", loss.item())
                for met in self.metric_ftns:
                    self.valid_metrics.update(met.__name__, met(output, target))
                self.writer.add_image("input", make_grid(data.cpu(), nrow=8, normalize=True))

        // add histogram of model parameters to the tensorboard
        for name, p in self.model.named_parameters():

Instances