def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
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