int32_t* values = new int32_t[1];
  values[0] = v;
  return TF_NewTensor(TF_INT32, nullptr, 0, values, num_bytes,
                      &Int32Deallocator, nullptr);
}

TF_Tensor* DoubleTensor(double v) {
  const int num_bytes = sizeof(double);
  double* values = new double[1];
  values[0] = v;
  return TF_NewTensor(TF_DOUBLE, nullptr, 0, values, num_bytes,
                      &DoubleDeallocator, nullptr);
}

       ++device_index) {
    auto device_value = absl::make_unique<DataType>();
    *device_value = values[device_index];
    std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> tensor(
        TF_NewTensor(
            datatype_enum, /*dims=*/nullptr, /*num_dims=*/0,
            device_value.release(), sizeof(DataType),
            [](void* data, size_t, void* arg) {
              delete reinterpret_cast<DataType*>(data);

      reinterpret_cast<float*>(tensorflow::cpu_allocator()->AllocateRaw(
          TF_TensorDefaultAlignment(), num_bytes));
  int64_t dims[] = {2, 3};
  bool deallocator_called = false;
  TF_Tensor* t = TF_NewTensor(TF_FLOAT, dims, 2, values, num_bytes,
                              &Deallocator, &deallocator_called);
  EXPECT_FALSE(deallocator_called);
  EXPECT_EQ(TF_FLOAT, TF_TensorType(t));
  EXPECT_EQ(2, TF_NumDims(t));

  dims.reserve(shape.dims());
  for (int i = 0; i < shape.dims(); ++i) {
    dims.push_back(shape.dim_size(i));
    nelems *= shape.dim_size(i);
  }
  CHECK_EQ(nelems, 0);
  return TF_NewTensor(
      dtype, reinterpret_cast<const int64_t*>(dims.data()), shape.dims(),
      reinterpret_cast<void*>(&empty), 0, [](void*, size_t, void*) {}, nullptr);
}

static void TF_Run_Helper(