def test_view_mixin_copies_data(adata, array_type: type, attr):
    N = 100
    adata = ad.AnnData(
        obs=pd.DataFrame(index=np.arange(N)), var=pd.DataFrame(index=np.arange(N))
    )

    X = array_type(sparse.eye(N, N).multiply(np.arange(1, N + 1)))
    if attr == "X":
        adata.X = X
    else:
        getattr(adata, attr)["arr"] = X

    view = adata[:50]

    if attr == "X":
        arr_view = view.X
    else:
        arr_view = getattr(view, attr)["arr"]

    arr_view_copy = arr_view.copy()

    if sparse.issparse(X):
        assert not np.shares_memory(arr_view.indices, arr_view_copy.indices)
        assert not np.shares_memory(arr_view.indptr, arr_view_copy.indptr)
        assert not np.shares_memory(arr_view.data, arr_view_copy.data)

        arr_view_copy.data[0] = -5
        assert not np.array_equal(arr_view_copy.data, arr_view.data)
    else:
        assert not np.shares_memory(arr_view, arr_view_copy)

        arr_view_copy[0, 0] = -5
        assert not np.array_equal(arr_view_copy, arr_view)
def _restore_checkpoint_and_maybe_run_saved_model_initializers(
    sess, saver, path):
  """Restores checkpoint values and SavedModel initializers if found."""
  # NOTE: All references to SavedModel refer to SavedModels loaded from the
  # load_v2 API (which does not require the `sess` argument).

  # If the graph contains resources loaded from a SavedModel, they are not
  # restored when calling `saver.restore`. Thus, the SavedModel initializer must
  # be called with `saver.restore` to properly initialize the model.

  # The SavedModel init is stored in the "saved_model_initializers" collection.
  # This collection is part of the MetaGraph's default_init_op, so it is already
  # called by MonitoredSession as long as the saver doesn't restore any
  # checkpoints from the working dir.
  saved_model_init_ops = ops.get_collection("saved_model_initializers")
  if saved_model_init_ops:
    sess.run(saved_model_init_ops)

  # The saver must be called *after* the SavedModel init, because the SavedModel
  # init will restore the variables from the SavedModel variables directory.
  # Initializing/restoring twice is not ideal but there's no other way to do it.
  saver.restore(sess, path)