def fit()

in ASLRecognition/scripts/train.py [0:0]

• 19 lines of code
• 2 McCabe index (conditional complexity)

def fit(model, dataloader):
    print('Training')
    model.train()
    running_loss = 0.0
    running_correct = 0
    for i, data in tqdm(enumerate(dataloader), total=int(len(train_data)/dataloader.batch_size)):
        data, target = data[0].to(device), data[1].to(device)
        optimizer.zero_grad()
        outputs = model(data)
        loss = criterion(outputs, target)
        running_loss += loss.item()
        _, preds = torch.max(outputs.data, 1)
        running_correct += (preds == target).sum().item()
        loss.backward()
        optimizer.step()

    train_loss = running_loss/len(dataloader.dataset)
    train_accuracy = 100. * running_correct/len(dataloader.dataset)

    print(f"Train Loss: {train_loss:.4f}, Train Acc: {train_accuracy:.2f}")

    return train_loss, train_accuracy