def test_set_varm_key(adata):
    init_hash = joblib.hash(adata)

    orig_varm_val = adata.varm["o"].copy()
    subset_varm = adata[:, :50]
    assert subset_varm.is_view
    subset_varm.varm["o"] = np.ones((50, 20))
    assert not subset_varm.is_view
    assert np.all(adata.varm["o"] == orig_varm_val)

    assert init_hash == joblib.hash(adata)
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