def _validate_class_data_shapes(self, data, val=True, validate_n_slices=False):
    """Standardize `sample_weight` and `class_labels` data. Same as
    :meth:`_validate_data_shapes`, except skips two validations:

        - `_validate_last_dims_match_outs_shape`; for `class_labels`, model
          output shapes can be same as input shapes as with autoencoders,
          but inputs can still have class labels, subjecting to `sample_weight`.
          `sample_weight` often won't share model output shape, as with e.g.
          multiclass classification, where individual classes aren't weighted.
        - `_equal_shapes`; per above, `data` entries may not have equal shapes.
    """
    return self._validate_data_shapes(data, val,
                                      validate_n_slices,
                                      validate_last_dims_match_outs_shape=False,
                                      validate_equal_shapes=False)