validation phase

            if phase == 'val':
                model.eval()
                with torch.no_grad():
                    for inputs, labels in dataloaders[phase]:
                        val_inputs = inputs.to(device)
                        val_labels = labels.to(device)

                        val_outputs = model(val_inputs)
                        val_loss = criterion(val_outputs, val_labels)
                        _, val_preds = torch.max(val_outputs, 1)

                        # statistics
                        val_running_loss += val_loss.item() * val_inputs.size(0)
                        val_running_corrects += torch.sum(val_preds == val_labels.data)