1, nullptr, 0, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(3, *(static_cast<int32_t*>(TF_TensorData(fetchValues1[0]))));
  TF_DeleteTensor(feedValues1[0]);
  TF_DeleteTensor(fetchValues1[0]);

  // Feed B and fetch (A + 2) + B.
  TF_Output feeds2[] = {TF_Output{b, 0}};
  TF_Output fetches2[] = {TF_Output{plusB, 0}};
  TF_Tensor* feedValues2[] = {Int32Tensor(4)};

    EXPECT_EQ(
        0, memcmp(TF_TensorData(t), TF_TensorData(tcopy), TF_TensorByteSize(t)))
        << tag;
    TF_DeleteTensor(tcopy);
  }

  TF_DeleteDeviceList(devices);
  TF_DeleteTensor(t);
  TFE_DeleteTensorHandle(hcpu);
  TFE_DeleteContext(ctx);
}

TEST(CAPI, TensorHandleCopyBetweenDevices) {
  TensorHandleCopyBetweenDevices(false);
}

    int max_values, TF_Status* status);

// Gets the TF_Tensor valued attribute of `attr_name` of `oper`.
//
// Allocates a new TF_Tensor which the caller is expected to take
// ownership of (and can deallocate using TF_DeleteTensor).
TF_CAPI_EXPORT extern void TF_OperationGetAttrTensor(TF_Operation* oper,
                                                     const char* attr_name,
                                                     TF_Tensor** value,

                  "`inputs` must have a single output. Node split3 has "
                  "3 outputs. Encountered while creating function 'MyFunc'"),
      std::string(TF_Message(s_)));

  TF_DeleteTensor(tensor_123);
}

TEST_F(CApiFunctionTest, FunctionWithWhileLoop) {
  // Inputs to the while loop and the function as a whole
  TF_Operation* feed1 = Placeholder(func_graph_, s_, "feed1");