def display_val()

in train.py [0:0]

• 15 lines of code
• 4 McCabe index (conditional complexity)

def display_val(model, loss_criterion, writer, index, dataset_val, opt):
    losses = []
    with torch.no_grad():
        for i, val_data in enumerate(dataset_val):
            if i < opt.validation_batches:
                output = model.forward(val_data)
                loss = loss_criterion(output['binaural_spectrogram'], output['audio_gt'])
                losses.append(loss.item()) 
            else:
                break
    avg_loss = sum(losses)/len(losses)
    if opt.tensorboard:
        writer.add_scalar('data/val_loss', avg_loss, index)
    print('val loss: %.3f' % avg_loss)
    return avg_loss