def train_one_epoch()

in source/sagemaker/src/package/data_privatization/container/train.py [0:0]

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

def train_one_epoch(model, iterator, optimizer, criterion):
    epoch_loss = 0
    epoch_acc = 0

    model.train()

    for batch in iterator:
        optimizer.zero_grad()

        predictions = model(batch.review).squeeze(1)

        loss = criterion(predictions, batch.sentiment)

        acc = binary_accuracy(predictions, batch.sentiment)

        loss.backward()

        optimizer.step()

        epoch_loss += loss.item()
        epoch_acc += acc.item()

    return epoch_loss / len(iterator), epoch_acc / len(iterator)