尝试在环回4

问题描述

我想向服务器添加身份验证。我在这里关注文档：https://loopback.io/doc/en/lb4/Authentication-tutorial.html

添加此注释@authenticate('jwt')时，出现以下错误：

Cannot start the application. TypeError: core_1.injectable is not a function
    at Object.<anonymous> (C:\Users\mshaham\projects\mevolve\user-service\node_modules\@loopback\authentication\src\providers\auth-action.provider.ts:116:2)
    at Module._compile (internal/modules/cjs/loader.js:1147:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:1167:10)
    at Module.load (internal/modules/cjs/loader.js:996:32)
    at Function.Module._load (internal/modules/cjs/loader.js:896:14)
    at Module.require (internal/modules/cjs/loader.js:1036:19)
    at require (internal/modules/cjs/helpers.js:72:18)
    at Object.<anonymous> (C:\Users\mshaham\projects\mevolve\user-service\node_modules\@loopback\authentication\src\providers\index.ts:6:1)
    at Module._compile (internal/modules/cjs/loader.js:1147:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:1167:10)
    at Module.load (internal/modules/cjs/loader.js:996:32)
    at Function.Module._load (internal/modules/cjs/loader.js:896:14)
    at Module.require (internal/modules/cjs/loader.js:1036:19)
    at require (internal/modules/cjs/helpers.js:72:18)
    at Object.<anonymous> (C:\Users\xxxxx\projects\xxxx\user-service\node_modules\@loopback\authentication\src\authentication.component.ts:8:1)
    at Module._compile (internal/modules/cjs/loader.js:1147:30)

解决方法

Node.js v13不受LoopBack 4或the Node.js team themselves的正式支持。还建议您坚持使用偶数或LTS版本。

将Node.js运行时更改为v10，v12或v14。

,

我发现了问题所在。在安装回送核心后几周，我安装了回送身份验证程序包。同时，核心软件包发布了一些重大更改。

因此，我所要做的就是使用for heldout_dataset in os.listdir(): # Create model base_model = tf.keras.applications.Xception(input_shape=IMG_SHAPE,include_top=False,weights='imagenet') # (Etc,adding layers) model = tf.keras.Model(inputs,outputs) # (Etc,loading some data that is not held out (ie,not the 'Fold')) train_data = tf.keras.preprocessing.image_dataset_from_directory(....) val_data = tf.keras.preprocessing.image_dataset_from_directory(....) model.fit(train_data,val_data) # (Etc,making predictions) # Clear Everything del train_data del model del base_model del val_data tf.keras.backend.clear_session() 更新我的软件包并解决了问题！