def test_modify_view_component(matrix_type, mapping_name):
    adata = ad.AnnData(
        np.zeros((10, 10)),
        **{mapping_name: dict(m=matrix_type(asarray(sparse.random(10, 10))))},
    )
    init_hash = joblib.hash(adata)

    subset = adata[:5, :][:, :5]
    assert subset.is_view
    m = getattr(subset, mapping_name)["m"]
    m[0, 0] = 100
    assert not subset.is_view
    assert getattr(subset, mapping_name)["m"][0, 0] == 100

    assert init_hash == joblib.hash(adata)
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)