return reinterpret_cast<::tensorflow::OpKernelContext*>(ctx)->step_id();
}

TF_Buffer* TF_OpKernelConstruction_GetNodeDef(TF_OpKernelConstruction* ctx,
                                              TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelConstruction*>(ctx);
  TF_Buffer* ret = TF_NewBuffer();
  status->status = MessageToBuffer(cc_ctx->def(), ret);
  if (!status->status.ok()) {

    // Test op list.
    TF_Buffer op_list_buf = TF_GetOpList(lib);
    tensorflow::OpList op_list;
    EXPECT_TRUE(op_list.ParseFromArray(op_list_buf.data, op_list_buf.length));
    ASSERT_EQ(op_list.op_size(), 1);
    EXPECT_EQ("TestCApi1", op_list.op(0).name());
    TF_DeleteLibraryHandle(lib);
  }
#endif  // !defined(TENSORFLOW_NO_SHARED_OBJECTS)
  {
    TF_Buffer* op_list_buffer = TF_GetAllOpList();

// Interprets the named kernel construction attribute as a
// tensorflow::NameAttrList and returns the serialized proto as TF_Buffer.
// `status` will be set. The caller takes ownership of the returned TF_Buffer
// (if not null) and is responsible for managing its lifetime.
TF_CAPI_EXPORT extern TF_Buffer* TF_OpKernelConstruction_GetAttrFunction(
    TF_OpKernelConstruction* ctx, const char* attr_name, TF_Status* status);

  // 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);

  {
    TF_Status* status = TF_NewStatus();
    TF_RegisterKernelBuilder(node_name, builder, status);
    EXPECT_EQ(TF_OK, TF_GetCode(status));
    TF_Buffer* buf = TF_GetRegisteredKernelsForOp(op_name, status);
    EXPECT_EQ(TF_OK, TF_GetCode(status));
    KernelList list;
    list.ParseFromArray(buf->data, buf->length);
    ASSERT_EQ(1, list.kernel_size());

    }
    tasks {
      key: 1
      value: "localhost:1"
    }
  }
}
job_name: "worker"
task_index: 1
protocol: "grpc"
)");

  TF_Status* status = TF_NewStatus();
  TF_Buffer* result = TFE_GetServerDef(expected_text_proto.c_str(), status);
  EXPECT_EQ(TF_GetCode(status), TF_OK);

  ServerDef actual;
  ASSERT_TRUE(actual.ParseFromArray(result->data, result->length));
  string actual_text_proto;

TF_CAPI_EXPORT extern TF_Buffer* TF_CreateConfig(
    unsigned char enable_xla_compilation, unsigned char gpu_memory_allow_growth,
    unsigned int num_cpu_devices);

// Create a serialized tensorflow.RunOptions proto, where RunOptions.trace_level
// is set to FULL_TRACE if `enable_full_trace` is non-zero, and NO_TRACE
// otherwise.
TF_CAPI_EXPORT extern TF_Buffer* TF_CreateRunOptions(

  TF_OpDefinitionBuilderAddOutput(builder, "output1: uint32");
  TF_Status* status = TF_NewStatus();
  TF_RegisterOpDefinition(builder, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_Buffer* op_list_buffer = TF_GetAllOpList();
  ::tensorflow::OpList op_list;
  op_list.ParseFromArray(op_list_buffer->data, op_list_buffer->length);
  bool found = false;
  for (const auto& op : op_list.op()) {

    func->record = new tensorflow::FunctionRecord(lib.function(i), {}, false);
    funcs[i] = func;
  }
  status->status = absl::OkStatus();
  return len;
}

void TF_FunctionToFunctionDef(TF_Function* func, TF_Buffer* output_func_def,
                              TF_Status* status) {
  status->status = MessageToBuffer(func->record->fdef(), output_func_def);
}