def test_view_delitem(attr):
    adata = gen_adata((10, 10))
    getattr(adata, attr)["to_delete"] = np.ones((10, 10))
    # Shouldn’t be a subclass, should be an ndarray
    assert type(getattr(adata, attr)["to_delete"]) is np.ndarray
    view = adata[5:7, :][:, :5]
    adata_hash = joblib.hash(adata)
    view_hash = joblib.hash(view)

    getattr(view, attr).__delitem__("to_delete")

    assert not view.is_view
    assert "to_delete" not in getattr(view, attr)
    assert "to_delete" in getattr(adata, attr)
    assert adata_hash == joblib.hash(adata)
    assert view_hash != joblib.hash(view)
def update_state(self, y_true, y_pred, sample_weight=None):
    sample_weight = _apply_mask(y_true, sample_weight, self._masked_tokens,
                                self._dtype)
    num_classes = tf.shape(y_pred)[-1]
    y_true = tf.reshape(y_true, [-1])
    y_pred = tf.reshape(y_pred, [-1, num_classes])
    sample_weight = tf.reshape(sample_weight, [-1])
    super().update_state(y_true, y_pred, sample_weight)