def test_set_var(adata, subset_func):
    init_hash = joblib.hash(adata)

    subset = adata[:, subset_func(adata.var_names)]

    new_var = pd.DataFrame(
        dict(a=np.ones(subset.n_vars), b=np.ones(subset.n_vars)),
        index=subset.var_names,
    )

    assert subset.is_view
    subset.var = new_var
    assert not subset.is_view
    assert np.all(subset.var == new_var)

    assert joblib.hash(adata) == init_hash
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)