2767c948afa434f863df3b5eb1946a032dfba588,spotlight/losses.py,,hinge_loss,#,86

Before Change

        The mean value of the loss function.
    

    return torch.mean(torch.clamp(negative_predictions -
                                  positive_predictions +
                                  1.0, 0.0))


def regression_loss(observed_ratings, predicted_ratings):
    

After Change

                       positive_predictions +
                       1.0, 0.0)

    if mask is not None:
        loss = loss * mask.float()

    return loss.mean()


def regression_loss(observed_ratings, predicted_ratings):

Instances