Gets root mse between the logarithms of the prediction and the truth.

def get_rmse_log(net, X_train, y_train):
    """Gets root mse between the logarithms of the prediction and the truth."""
    num_train = X_train.shape[0]
    clipped_preds = nd.clip(net(X_train), 1, float('inf'))
    return np.sqrt(2 * nd.sum(square_loss(
        nd.log(clipped_preds), nd.log(y_train))).asscalar() / num_train)