//        searchName = Srl.substringFirstRear(classificationName, ".");
        //    } else {
        //        return null;
        //    }
        //}
        //try {
        //    return CDef.DefMeta.valueOf(searchName);
        //} catch (IllegalArgumentException ignored) { // not found
        //    return null; // handled later
        //}
    }

    @Override

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());
  status->status = g->graph.AddGradientDef(std::move(gdef));
}

int TF_GraphNumFunctions(TF_Graph* g) {
  tensorflow::mutex_lock l(g->mu);
  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,

  for (const FunctionDef& fdef : fdef_lib.function()) {
    // Make a copy so that we can mutate it.
    FunctionDef fdef_to_load = fdef;
    if (mutate_proto_func) {
      (*mutate_proto_func)(&fdef_to_load);
    }
    VLOG(1) << "Adding func to graph: " << fdef_to_load.DebugString();
    std::vector<char> binary_proto_buf(fdef_to_load.ByteSizeLong());
    fdef_to_load.SerializeToArray(binary_proto_buf.data(),

}

void TFE_ContextAddFunction(TFE_Context* ctx, TF_Function* function,
                            TF_Status* status) {
  auto fdef_or = function->record->mutable_fdef();
  if (!fdef_or.ok()) {
    status->status = fdef_or.status();
    return;
  }

  AnnotateEagerRuntimeConstructionContext(*fdef_or.value());
  status->status = tensorflow::unwrap(ctx)->AddFunctionDefWithStackTraces(

  tensorflow::GraphDef graph_def_proto;
  ASSERT_TRUE(tensorflow::ParseProtoUnlimited(&graph_def_proto, graph_def->data,
                                              graph_def->length));
  TF_Buffer graph_def_buffer;
  graph_def_buffer.data = reinterpret_cast<const void*>(&graph_def_proto);
  graph_def_buffer.length = sizeof(tensorflow::GraphDef*);
  TF_ImportGraphDefResults* results =

  return nullptr;
#else
  mutex_lock l(api_def_map->lock);
  if (!api_def_map->update_docs_called) {
    api_def_map->api_def_map.UpdateDocs();
    api_def_map->update_docs_called = true;
  }
  string name_str(name, name_len);
  const auto* api_def = api_def_map->api_def_map.GetApiDef(name_str);
  if (api_def == nullptr) {
    return nullptr;
  }

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());
  return absl::OkStatus();
}
}  // namespace graph
}  // namespace tracing

async def context_b(state: dict = Depends(context_a)):
    state["context_b"] = "started b"
    try:
        yield state
    finally:
        state["context_b"] = f"finished b with a: {state['context_a']}"


@app.get("/async")
async def get_async(state: str = Depends(asyncgen_state)):
    return state


@app.get("/sync")
async def get_sync(state: str = Depends(generator_state)):

            ]
        }
    )


def test_query_optional():
    response = client.get("/query/optional")
    assert response.status_code == 200
    assert response.json() == "foo bar"


def test_query_optional_query_baz():
    response = client.get("/query/optional?query=baz")
    assert response.status_code == 200
    assert response.json() == "foo bar baz"


def test_query_optional_not_declared_baz():

      "      value: 'add2:z:0'"
      "    }",
      &def));
  return def.SerializeAsString();
}

void TestFunctionWithPackedInput(const bool remote) {
  tensorflow::ServerDef server_def = GetServerDef(3);

  // This server def has the task index set to 0.
  string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;