def test_deepcopy_subset(adata, spmat: type):
    adata.obsp["arr"] = np.zeros((adata.n_obs, adata.n_obs))
    adata.obsp["spmat"] = spmat((adata.n_obs, adata.n_obs))

    adata = deepcopy(adata[:10].copy())

    assert isinstance(adata.obsp["arr"], np.ndarray)
    assert not isinstance(adata.obsp["arr"], ArrayView)
    np.testing.assert_array_equal(adata.obsp["arr"].shape, (10, 10))

    assert isinstance(adata.obsp["spmat"], spmat)
    assert not isinstance(
        adata.obsp["spmat"],
        SparseCSRView if spmat is sparse.csr_matrix else SparseCSCView,
    )
    np.testing.assert_array_equal(adata.obsp["spmat"].shape, (10, 10))
def _apply_mask(y_true, sample_weight, masked_tokens, dtype):
  if sample_weight is None:
    sample_weight = tf.ones_like(y_true, dtype)
  else:
    sample_weight = tf.cast(sample_weight, dtype)
  for token in masked_tokens:
    mask = tf.cast(tf.not_equal(y_true, token), dtype)
    sample_weight = sample_weight * mask
  return sample_weight