EXPECT_FALSE(root.status().ok());
}

TEST(CCOpTest, InvalidFinalize) {
  Scope root = Scope::NewRootScope();
  auto read_up_to =
      ops::ReaderReadUpTo(root, Variable(root, {}, DT_STRING),
                          Variable(root, {}, DT_STRING), static_cast<int32>(2));
  EXPECT_FALSE(root.status().ok());
  auto err_msg = std::string(root.status().message());
  EXPECT_NE(err_msg.find("'num_records' passed int32 expected int64"),

                                      const std::string& s,
                                      ImmediateTensorHandlePtr* out) {
  int64_t flat_shape[] = {1};
  AbstractTensorPtr tensor(ctx->CreateTensor(DT_STRING, flat_shape));
  if (tensor.get() == nullptr) {
    return errors::Internal(
        "Failed to create vector string tensor for checkpoint restore");
  }
  // Use placement new to construct the string, since we don't have

  Tensor t(first.tensor.dtype(), shape);

  // Collate the constituent Tensors.
  size_t offset = 0;
  for (auto const& e : v) {
    Tensor elem = e.tensor;
    if (first.tensor.dtype() == DT_STRING) {
      for (int i = 0; i < elem.NumElements(); ++i) {
        t.flat<tstring>()(offset + i) = elem.flat<tstring>()(i);
      }
      offset += elem.NumElements();
    } else {

  TF_RETURN_WITH_CONTEXT_IF_ERROR(
      bundle_reader->Lookup(kObjectGraphProtoKey, &object_graph_tensor),
      "SavedModel checkpoint does not contain object graph.");
  if (object_graph_tensor.dtype() != DT_STRING ||
      object_graph_tensor.dims() != 0 ||
      object_graph_tensor.NumElements() != 1) {
    return absl::Status(
        absl::StatusCode::kFailedPrecondition,