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python - 即使在安装后导入 tensorflow 包也会出现错误消息

问题描述

今天是个好日子。我从互联网上得到了一个模块，这是一个关于 NMT 的模块。在模块中，我有一个 tensorflow 的导入，但不幸的是，即使在我的系统中使用 pip 安装了 tensorflow，我仍然会收到错误消息。这是错误

from tensorflow.keras.models import load_model

ModuleNotFoundError: No module named 'tensorflow'

模块 hello_app.py 如下：

from flask import Flask
from flask import request

from flask import jsonify

import uuid
import os
from tensorflow.keras.models import load_model
import numpy as np

EXPECTED = {
  "cylinders":{"min":3,"max":8},
  "displacement":{"min":68.0,"max":455.0},
  "horsepower":{"min":46.0,"max":230.0},
  "weight":{"min":1613,"max":5140},
  "acceleration":{"min":8.0,"max":24.8},
  "year":{"min":70,"max":82},
  "origin":{"min":1,"max":3}

}

# Load neural network when Flask boots up
model = load_model(os.path.join("../dnn/","mpg_model.h5"))

@app.route('/api/mpg', methods=['POST'])
def calc_mpg():
    content = request.json
    errors = []
    
    for name in content:
        if name in EXPECTED:
            expected_min = EXPECTED[name]['min']
            expected_max = EXPECTED[name]['max']
            value = content[name]
            if value < expected_min or value > expected_max:
                errors.append(f"Out of bounds: {name}, has value of: {value}, but should be between {expected_min} and {expected_max}.")
        else:
            errors.append(f"Unexpected field: {name}.")

# Check for missing input fields
           for name in EXPECTED:
               if name not in content:
                   errors.append(f"Missing value: {name}.")



  if len(errors) <1:
        x = np.zeros( (1,7) )


     # Predict
   x[0,0] = content['cylinders']
   x[0,1] = content['displacement'] 
   x[0,2] = content['horsepower']
   x[0,3] = content['weight']
   x[0,4] = content['acceleration'] 
   x[0,5] = content['year']
   x[0,6] = content['origin']



   pred = model.predict(x)
   mpg = float(pred[0])
   response = {"id":str(uuid.uuid4()),"mpg":mpg,"errors":errors}
   else:
       response = {"id":str(uuid.uuid4()),"errors":errors}

   print(content['displacement'])
   return jsonify(response)

   if __name__ == '__main__':
       app.run(host= '0.0.0.0',debug=True)

请非常感谢您的回答。谢谢你。

这是我获得代码的 github 存储库 https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_13_01_flask.ipynb

标签： pythontensorflow

解决方案

为避免包或版本冲突，可以使用虚拟环境。

pip install virtualenv
virtualenv -p /usr/bin/python3 tf
source tf/bin/activate 
tf$ pip install tensorflow

如果你有 Anaconda 或 conda

#Set Up Anaconda Environments
conda create --name tf python=3

#Activate the new Environment
source activate tf
tf$pip install tensorflow

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