Flask和Keras模型错误"_thread._local"对象没有属性“值"? [英] Flask and Keras model Error ''_thread._local' object has no attribute 'value''?

问题描述

我正在使用以下内容: python 3.6.4

I am using the following: python 3.6.4

烧瓶= 1.1.1，

Keras = 2.3.0，

Keras = 2.3.0,

TensorFlow = 1.14.0， 我有一个Flask服务器，可以从客户端获取图片.我将Keras模型与TensorFlow后端结合使用，我尝试从预先训练的模型中获得预测.

TensorFlow = 1.14.0, I have a Flask server that gets pictures from the clients. using Keras model with a TensorFlow back-end I try to get a prediction from a pre-trained model.

我正在使用以下函数上传模型(作为课程的一部分)

I am using the following function to upload the model( as part of a class)

 model_path = self.conf["model_path"] // path in conf to model
 self.model = load_model(model_path)  // uploading the model
 self.model._make_predict_function()
 p_log.info("model had been upload successfully ")

并且我使用以下代码进行预测:

and I use the following line for prediction:

cm_prediction = self.model.predict([face, reye, leye, fg])[0]

直到今天，我还没有任何问题，总能得到一个预测. 现在我遇到以下错误:

Until today I didn't have any problem, always got a prediction. now I get the following error:

Traceback (most recent call last):
  File "D:\code_project\path to project", line 75, in predict
    cm_prediction = self.model.predict([face, reye, leye, fg])[0]
  File "D:\code_project\path to project", line 1462, in predict
    callbacks=callbacks)
  File "D:\code_project\predictserver\venv\lib\site-packages\keras\engine\training_arrays.py", line 276, in predict_loop
    callbacks.model.stop_training = False
  File "D:\code_project\predictserver\venv\lib\site-packages\keras\engine\network.py", line 323, in __setattr__
    super(Network, self).__setattr__(name, value)
  File "D:\code_project\predictserver\venv\lib\site-packages\keras\engine\base_layer.py", line 1215, in __setattr__
    if not _DISABLE_TRACKING.value:
AttributeError: '_thread._local' object has no attribute 'value'

我有一个运行的简单Flask服务器:

I have a simple Flask server running:

if __name__ == '__main__':
    pre = predictor()
    # app.run(debug=True)
    app.run(host='0.0.0.0', port=12345)

该模型始终处于上传状态.

The model is always being uploaded.

如果我在没有Flask服务器的情况下运行程序 ，因此进行了手动输入，我得到了一个预测，但是当服务器启动后，出现错误，我停止获取预测

If I am running the program without the Flask server, hence giving manually input, I get a prediction, but as soon as the server is on the error appears and I stop getting a predictions

我试图在网络上查找一些类似的问题，但没有发现任何问题，如果有人知道问题所在以及如何解决问题，我将不胜感激.

I tried to look on the web for some similar problem but didnt found any, if someone knows what the problem and how to solve it, I will appreciate sharing it.

推荐答案

所以，经过漫长的夜晚， Keras已在19年9月17日发布了新版本2.3.0. 作为修订版本的一部分，我更新了所有库，其中包括Keras.自从我做到了，消息就出现了.

So after a long night, Keras had released a new version 2.3.0 in Sep 17,19. As part of revision update I did, I updated all libraries, Keras among them. Since I did it the message appeared.

我降级到Keras 2.2.5之后，问题消失了.

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