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

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

    new_obs = pd.DataFrame(
        dict(a=np.ones(subset.n_obs), b=np.ones(subset.n_obs)),
        index=subset.obs_names,
    )

    assert subset.is_view
    subset.obs = new_obs
    assert not subset.is_view
    assert np.all(subset.obs == new_obs)

    assert joblib.hash(adata) == init_hash
def _compute_reg_grads(gen_grads, disc_vars):
  """Compute gradients norm (this is an upper-bpund of the full-batch norm)."""
  gen_norm = tf.accumulate_n([tf.reduce_sum(u * u) for u in gen_grads])
  disc_reg_grads = tf.gradients(gen_norm, disc_vars)
  return disc_reg_grads