8a70c277c355fe734a01fe58baafdc2dc5164205,OpenNMT/train.py,,eval,#Any#Any#Any#,122

Before Change

        loss = criterion.forward(outputs, tgt)

    model.train()
    return math.exp(loss / data.len)


def trainModel(model, trainData, validData, dataset):
    print(model)

After Change

    total_words = 0

    model.eval()
    for i in range(len(data)):
        batch = data[i]
        outputs = model(batch)
        loss = criterion(outputs, batch[1])
        total_loss += loss.data[0]
        total_words += batch[1].data.gt(onmt.Constants.EOS).sum()

    model.train()
    return total_loss / total_words

Instances