def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
def _model_variable_scope(self):
    """Returns a variable scope that the model should be created under.

    If self.dtype is a castable type, model variable will be created in fp32
    then cast to self.dtype before being used.

    Returns:
      A variable scope for the model.
    """

    return tf.compat.v1.variable_scope(
        'resnet_model',
        custom_getter=self._custom_dtype_getter,
        reuse=tf.AUTO_REUSE)