def test_view_delattr(attr, subset_func):
    base = gen_adata((10, 10))
    orig_hash = joblib.hash(base)
    subset = base[subset_func(base.obs_names), subset_func(base.var_names)]
    empty = ad.AnnData(obs=subset.obs[[]], var=subset.var[[]])

    delattr(subset, attr)

    assert not subset.is_view
    # Should now have same value as default
    assert_equal(getattr(subset, attr), getattr(empty, attr))
    assert orig_hash == joblib.hash(base)  # Original should not be modified
def update_model(model, disc_grads, gen_grads, disc_opt, gen_opt,
                 global_step, update_scale):
  """Update model with gradients."""

  disc_vars, gen_vars = model.get_variables()

  with tf.control_dependencies(gen_grads + disc_grads):
    disc_update_op = disc_opt.apply_gradients(
        zip(_scale_vars(update_scale, disc_grads),
            disc_vars))

    gen_update_op = gen_opt.apply_gradients(
        zip(_scale_vars(update_scale, gen_grads),
            gen_vars),
        global_step=global_step)

    update_op = tf.group([disc_update_op, gen_update_op])

  return update_op