// a different TFE context for each thread of execution (for running graph
  // functions, and their send/recvs corountines).
  config.set_inter_op_parallelism_threads(1);

  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(config, ret));
  return ret;
}

TF_Buffer* TF_CreateRunOptions(unsigned char enable_full_trace) {
  tensorflow::RunOptions options;
  if (enable_full_trace) {

         node_def.input_size() == 1 && node_def.input(0) == input;
}

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def) {
  TF_Status* s = TF_NewStatus();
  TF_Buffer* buffer = TF_NewBuffer();
  TF_GraphToGraphDef(graph, buffer, s);
  bool ret = TF_GetCode(s) == TF_OK;
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  if (ret) ret = graph_def->ParseFromArray(buffer->data, buffer->length);

  auto* cell1 = TFE_MonitoringGetCellSampler1(sampler1, "foo");
  TFE_MonitoringSamplerCellAdd(cell1, 1.0);
  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}));

  TF_DeleteSessionOptions(opt);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TF_Buffer* run_options = TF_NewBufferFromString("", 0);
  TF_Buffer* run_metadata = TF_NewBuffer();
  TF_Run(session, run_options, nullptr, nullptr, 0, nullptr, nullptr, 0,
         nullptr, 0, run_metadata, s);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s)) << TF_Message(s);

    func_ = TF_FunctionImportFunctionDef(buf.data(), buf.size(), s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  void GetAttr(const char* attr_name, AttrValue* out_attr) {
    TF_Buffer* attr_buf = TF_NewBuffer();
    TF_FunctionGetAttrValueProto(func_, attr_name, attr_buf, s_);
    ASSERT_TRUE(out_attr->ParseFromArray(attr_buf->data, attr_buf->length));
    TF_DeleteBuffer(attr_buf);
  }

  tensorflow::OpRegistry::Global()->GetRegisteredOps(&op_defs);
  tensorflow::OpList op_list;
  for (const auto& op : op_defs) {
    *(op_list.add_op()) = op;
  }
  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(op_list, ret));
  return ret;
}

// --------------------------------------------------------------------------
// ListDevices & SessionListDevices API

                                                          size_t* pos);

// Write out a serialized representation of `graph` (as a GraphDef protocol
// message) to `output_graph_def` (allocated by TF_NewBuffer()).
// `output_graph_def`'s underlying buffer will be freed when TF_DeleteBuffer()
// is called.
//
// May fail on very large graphs in the future.
TF_CAPI_EXPORT extern void TF_GraphToGraphDef(TF_Graph* graph,

  int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteOp(matmul);
  TFE_DeleteTensorHandle(m);
  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(