TF_OperationDescription* reduce_desc =
      TF_NewOperation(body.get(), "CollectiveReduce", "CollectiveReduce");
  TF_SetAttrType(reduce_desc, "T", TF_FLOAT);
  TF_SetAttrInt(reduce_desc, "group_size", group_size);
  TF_SetAttrInt(reduce_desc, "group_key", 0);
  TF_SetAttrInt(reduce_desc, "instance_key", 0);

  const std::string merge_op("Mul");
  TF_SetAttrString(reduce_desc, "merge_op", merge_op.c_str(),

      0, graph, s, ::tensorflow::strings::StrCat(name, "_const0").c_str());
  TF_OperationDescription* desc = TF_NewOperation(graph, "Split", name);
  TF_AddInput(desc, {zero, 0});
  TF_AddInput(desc, {input, 0});
  TF_SetAttrInt(desc, "num_split", 3);
  TF_SetAttrType(desc, "T", TF_INT32);
  // Set device to CPU since there is no version of split for int32 on GPU
  // TODO(iga): Convert all these helpers and tests to use floats because

    EXPECT_EQ(list[i], string(static_cast<const char*>(values[i]), lens[i]))
        << i;
  }
}

TEST_F(CApiAttributesTest, Int) {
  auto desc = init("int");
  TF_SetAttrInt(desc, "v", 31415);

  auto oper = TF_FinishOperation(desc, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_TF_META("v", -1, TF_ATTR_INT, -1);

  int64_t value;

                                                const size_t* lengths,
                                                int num_values);
TF_CAPI_EXPORT extern void TF_SetAttrInt(TF_OperationDescription* desc,
                                         const char* attr_name, int64_t value);
TF_CAPI_EXPORT extern void TF_SetAttrIntList(TF_OperationDescription* desc,

    v.reserve(num_values);
    for (int i = 0; i < num_values; ++i) {
      v.emplace_back(static_cast<const char*>(values[i]), lengths[i]);
    }
    desc->node_builder.Attr(attr_name, v);
  }
}

void TF_SetAttrInt(TF_OperationDescription* desc, const char* attr_name,
                   int64_t value) {
  desc->node_builder.Attr(attr_name, static_cast<int64_t>(value));
}