def test_deepcopy_subset(adata, spmat: type):
    adata.obsp["arr"] = np.zeros((adata.n_obs, adata.n_obs))
    adata.obsp["spmat"] = spmat((adata.n_obs, adata.n_obs))

    adata = deepcopy(adata[:10].copy())

    assert isinstance(adata.obsp["arr"], np.ndarray)
    assert not isinstance(adata.obsp["arr"], ArrayView)
    np.testing.assert_array_equal(adata.obsp["arr"].shape, (10, 10))

    assert isinstance(adata.obsp["spmat"], spmat)
    assert not isinstance(
        adata.obsp["spmat"],
        SparseCSRView if spmat is sparse.csr_matrix else SparseCSCView,
    )
    np.testing.assert_array_equal(adata.obsp["spmat"].shape, (10, 10))
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)