}
  absl::Status SetAttrFunctionName(const char* attr_name, const char* value,
                                   size_t length) override {
    tensorflow::NameAttrList func_name;
    func_name.set_name(string(value, value + length));
    op_->node_builder.Attr(attr_name, func_name);
    return absl::OkStatus();
  }
  absl::Status SetAttrTensor(const char* attr_name,
                             AbstractTensorInterface* tensor) override {

  delete lib_handle;
}

void TF_GraphRemoveFunction(TF_Graph* g, const char* func_name,
                            TF_Status* status) {
  tensorflow::mutex_lock l(g->mu);
  status->status = g->graph.mutable_flib_def()->RemoveFunction(func_name);

}

void TF_SetAttrFuncName(TF_OperationDescription* desc, const char* attr_name,
                        const char* value, size_t length) {
  tensorflow::NameAttrList func_name;
  func_name.set_name(string(value, value + length));
  desc->node_builder.Attr(attr_name, func_name);
}

void TF_SetAttrShape(TF_OperationDescription* desc, const char* attr_name,
                     const int64_t* dims, int num_dims) {

func testAddr2Line(t *testing.T, dbgExePath, addr string) {
	funcName, srcPath, srcLineNo := runAddr2Line(t, dbgExePath, addr)
	if symName != funcName {
		t.Fatalf("expected function name %v; got %v", symName, funcName)
	}
	fi1, err := os.Stat("addr2line_test.go")
	if err != nil {
		t.Fatalf("Stat failed: %v", err)
	}

	// Debug paths are stored slash-separated, so convert to system-native.
	srcPath = filepath.FromSlash(srcPath)

		reqPath := r.URL.RawPath
		if reqPath == "" {
			reqPath = r.URL.Path
		}

		// Calculate function name
		funcName := tc.FuncName
		if funcName == "" {
			funcName = "<unknown>"
		}

		t := madmin.TraceInfo{
			TraceType: tt,
			FuncName:  funcName,
			NodeName:  nodeName,
			Time:      reqStartTime,
			Duration:  reqEndTime.Sub(respRecorder.StartTime),
			Path:      reqPath,

func getSource(level int) string {
	pc, file, lineNumber, ok := runtime.Caller(level)
	if ok {
		// Clean up the common prefixes
		file = trimTrace(file)
		_, funcName := filepath.Split(runtime.FuncForPC(pc).Name())
		return fmt.Sprintf("%v:%v:%v()", file, lineNumber, funcName)
	}
	return ""
}

// getTrace method - creates and returns stack trace
func getTrace(traceLevel int) []string {
	var trace []string

        "Encountered while processing input ", i, " into function '", fn_name,
        "'");
    TF_RETURN_WITH_CONTEXT_IF_ERROR(ValidateNonRefOutput(node, idx),
                                    "Encountered while processing input ", i,
                                    " into function '", fn_name, "'");

    input_tensors->emplace_back(node, idx);

    const auto& iter = input_nodes->find(node);

UserInDB(
    username="john",
    password="secret",
    email="******@****.***",
    full_name=None,
)
```

或更精准，直接把可能会用到的内容与 `user_dict` 一起使用：

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### 用其它模型中的内容生成 Pydantic 模型

UserInDB(
    username="john",
    password="secret",
    email="******@****.***",
    full_name=None,
)
```

⚖️ 🌅 ⚫️❔, ⚙️ `user_dict` 🔗, ⏮️ ⚫️❔ 🎚 ⚫️ 💪 ✔️ 🔮:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### Pydantic 🏷 ⚪️➡️ 🎚 ➕1️⃣

    password="secret",
    email="******@****.***",
    full_name=None,
)
```

Or more exactly, using `user_dict` directly, with whatever contents it might have in the future:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```