namespace {

using ::tensorflow::string;

// Add the values of three variables on three different tasks.
string AddVariablesFunction() {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"
      "      }"
      "      output_arg {"

    const char* text_proto,
    std::function<void(FunctionDef*)>* mutate_proto_func, TF_Status* status) {
  tensorflow::GraphDef gdef;
  if (!tensorflow::protobuf::TextFormat::ParseFromString(text_proto, &gdef)) {
    status->status = tensorflow::errors::Internal(
        "Invalid text proto for GraphDef: ", text_proto);
    return {};
  }
  const auto& fdef_lib = gdef.library();

  TFE_MonitoringSamplerCellAdd(cell1, 2.0);
  TF_Buffer* result1 = TF_NewBuffer();
  TFE_MonitoringSamplerCellValue(cell1, result1);
  tensorflow::HistogramProto histogram1;
  EXPECT_TRUE(histogram1.ParseFromString(
      {reinterpret_cast<const char*>(result1->data), result1->length}));
  EXPECT_EQ(histogram1.sum(), 3.0);
  TF_DeleteBuffer(result1);
  TFE_MonitoringDeleteSampler1(sampler1);

  TF_Buffer* b = TF_NewBuffer();
  TFE_ContextExportRunMetadata(ctx, b, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  tensorflow::RunMetadata rm;
  EXPECT_TRUE(
      rm.ParseFromString({reinterpret_cast<const char*>(b->data), b->length}));
  TF_DeleteBuffer(b);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  ASSERT_EQ(1, num_retvals);

  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Sanity check returned OpDef
  string data(static_cast<const char*>(buffer->data), buffer->length);
  OpDef op_def;
  op_def.ParseFromString(data);
  EXPECT_EQ(op_def.name(), func_name_);
  EXPECT_EQ(op_def.input_arg_size(), 1);
  EXPECT_EQ(op_def.output_arg_size(), 1);
  EXPECT_FALSE(op_def.is_stateful());

  TF_DeleteBuffer(buffer);
}

          "shape ",
          dst->shape().DebugString());
    }
    *dst = tensorflow::Tensor(tensorflow::DT_RESOURCE, dst->shape());
    if (!dst->scalar<tensorflow::ResourceHandle>()().ParseFromString(
            string(static_cast<const char*>(tensor_interface->Data()),
                   tensor_interface->ByteSize()))) {
      return InvalidArgument(