def METHOD_NAME(self):
    """Test if output is correct for the sLCWA training loop use case."""
    # Create dummy sLCWA labels
    ones = torch.ones(self.batch_size, 1)
    zeros = torch.zeros(self.batch_size, 1)
    labels = torch.cat([ones, zeros], dim=0)
    # Apply label smoothing
    smooth_labels = apply_label_smoothing(labels=labels, epsilon=self.epsilon, num_classes=self.num_entities)
    exp_true = 1.0 - self.epsilon
    np.testing.assert_allclose(smooth_labels[: self.batch_size], exp_true, rtol=self.relative_tolerance)
    exp_false = self.epsilon / (self.num_entities - 1.0)
    np.testing.assert_allclose(smooth_labels[self.batch_size :], exp_false, rtol=self.relative_tolerance)