@Test
    public void test_init_nofile() {
        ComponentUtil.setFessConfig(new FessConfig.SimpleImpl() {
            @Override
            public String getOsddLinkEnabled() {
                return "auto";
            }

            @Override
            public String getSsoType() {
                return "none";
            }
        });
        final OsddHelper osddHelper = new OsddHelper();

        "colorMode": "value",
        "graphMode": "area",
        "justifyMode": "auto",
        "orientation": "auto",
        "reduceOptions": {
          "calcs": [
            "mean"
          ],
          "fields": "",
          "values": false
        },
        "showPercentChange": false,
        "text": {},
        "textMode": "auto",
        "wideLayout": true
      },
      "pluginVersion": "10.4.0",

  tensorflow::mutex_lock c(graph->mu);
  const auto& debug_str = graph->graph.ToGraphDefDebug().DebugString();
  *len = debug_str.size();
  char* ret = static_cast<char*>(malloc(*len + 1));
  memcpy(ret, debug_str.c_str(), *len + 1);
  return ret;
}

char* TF_FunctionDebugString(TF_Function* func, size_t* len) {
  const auto& debug_str = DebugString(func->record->fdef());
  *len = debug_str.size();

TEST(CAPI, MonitoringSampler0) {
  TF_Status* status = TF_NewStatus();
  auto* buckets = TFE_MonitoringNewExponentialBuckets(1.0, 2.0, 2);
  auto* sampler =
      TFE_MonitoringNewSampler0("test/sampler", buckets, status, "test");
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  auto* cell = TFE_MonitoringGetCellSampler0(sampler);
  TFE_MonitoringSamplerCellAdd(cell, 1.0);
  auto* collection_registry = monitoring::CollectionRegistry::Default();

  return new TFE_Executor(&tensorflow::unwrap(ctx)->Executor());
}

void TFE_HostAddressSpace(TFE_Context* ctx, TF_Buffer* buf) {
  auto address_space = tensorflow::DeviceNameUtils::AddressSpace(
      tensorflow::unwrap(ctx)->HostCPUParsedName());
  auto str = tensorflow::DeviceNameUtils::ParsedNameToString(address_space);
  void* data = tensorflow::port::Malloc(str.length());

                         size_t length) {
  auto s = tensorflow::unwrap(op)->SetAttrString(
      attr_name, static_cast<const char*>(value), length);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name, int64_t value) {
  auto s = tensorflow::unwrap(op)->SetAttrInt(attr_name, value);
  if (!s.ok()) {

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  auto* placeholder_t =
      TF_AddFunctionParameter(graph_ctx, TF_FLOAT, {-1, nullptr}, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  // Build an abstract operation.
  auto* add_op = TF_NewAbstractOp(graph_ctx);
  TF_AbstractOpSetOpType(add_op, "Add", status.get());

using tensorflow::gtl::ArraySlice;

namespace tensorflow {
namespace tracing {
namespace graph {

class GraphContext;
class GraphOperation;
class GraphTensor;

auto& kUnknownDim = shape_inference::InferenceContext::kUnknownDim;
auto& kUnknownRank = shape_inference::InferenceContext::kUnknownRank;

// GraphTensor wraps a `TF_Output`, i.e. a pointer to TF_Operation and the index
// into the list of outputs for the operation.

  if (dlMTensor->deleter != nullptr) {
    dlMTensor->deleter(dlMTensor);
  }
}

void* TFE_HandleToDLPack(TFE_TensorHandle* h, TF_Status* status) {
  auto tf_dlm_context = GetDlContext(h, status);
  if (!status->status.ok()) {
    return nullptr;
  }

  auto* tf_dlm_data = TFE_TensorHandleDevicePointer(h, status);
  if (!status->status.ok()) {
    return nullptr;
  }

                                    " into function '", fn_name, "'");

    input_tensors->emplace_back(node, idx);

    const auto& iter = input_nodes->find(node);
    if (iter == input_nodes->end()) {
      input_nodes->insert({node, {idx}});
    } else {
      auto& indices = iter->second;
      if (std::find(indices.begin(), indices.end(), idx) != indices.end()) {