def test_view_retains_ndarray_subclass():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata.obsm["foo"] = np.zeros((10, 5)).view(NDArraySubclass)

    view = adata[:5, :]

    assert isinstance(view.obsm["foo"], NDArraySubclass)
    assert view.obsm["foo"].shape == (5, 5)
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