}
  return op_reg_data->op_def.is_stateful();
}

void TF_InitMain(const char* usage, int* argc, char*** argv) {
  tensorflow::port::InitMain(usage, argc, argv);
}

int TF_PickUnusedPortOrDie() {
  return tensorflow::internal::PickUnusedPortOrDie();
}

TFE_TensorHandle* TFE_NewTensorHandleFromScalar(TF_DataType data_type,
                                                void* data, size_t len,

            .NewSubScope(child_scope_name);

    if (dx != nullptr) {
      std::vector<tensorflow::Output> dx_arg = OutputsFromTFOutputs(dx, ny);
      status->status =
          AddSymbolicGradients(scope, y_arg, x_arg, dx_arg, &dy_arg);
    } else {
      status->status = AddSymbolicGradients(scope, y_arg, x_arg, &dy_arg);
    }

    // Update g->name_map with the name_map from the scope, which will contain

    void (*deallocator)(void* data, size_t len, void* arg),
    void* deallocator_arg, TF_Status* status) {
  tensorflow::Device* device = nullptr;
  tensorflow::EagerContext* context =
      tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));
  status->status = context->FindDeviceFromName(device_name, &device);
  if (!status->status.ok()) {
    deallocator(data, len, deallocator_arg);
    status->status =

  EXPECT_EQ(TF_CANCELLED, TF_GetCode(s));
  EXPECT_EQ(string("cancel"), TF_Message(s));
  TF_DeleteStatus(s);
}

void Deallocator(void* data, size_t, void* arg) {
  tensorflow::cpu_allocator()->DeallocateRaw(data);
  *reinterpret_cast<bool*>(arg) = true;
}

TEST(CAPI, Tensor) {
  const int num_bytes = 6 * sizeof(float);
  float* values =
      reinterpret_cast<float*>(tensorflow::cpu_allocator()->AllocateRaw(