title: Unable to use configparser in ai-platform custom prediction
body: <p>I'm looking at a way to use <code>configparser</code> in my predictor code for custom prediction routine.
  I tried following code snippet</p>
  
  <p><strong>common.cfg</strong></p>
  
  <pre><code>[MODEL]
  VERSION=config-true
  </code></pre>
  
  <p><strong>setup.py</strong></p>
  
  <pre><code>from setuptools import setup
  
  REQUIRED_PACKAGES = [
      'joblib==0.13.0'
  ]
  
  setup(
      name='test',
      description='Custom prediction routine',
      version=0.1,
      install_requires=REQUIRED_PACKAGES,
      scripts=['src/predictor.py', 'config/common.cfg']
  )
  </code></pre>
  
  <p><strong>predictor.py</strong></p>
  
  <pre><code>import os
  import joblib
  import subprocess
  import configparser
  
  class CustomPredictor(object):
      def __init__(self, model, config):
          self._model = model
          self._config = config
  
      def predict(self, instances, **kwargs):
          version_value = self._config.get('MODEL', 'VERSION', fallback='config-false')
          print(f'version value = {version_value}', flush=True) # printing config-false
  
          preprocessed_input = self._preprocess(instances)
  
          score = self._model.predict(preprocessed_input)
  
          print(f'predicted score {score}', flush=True)
          return score.to_list()
  
      @classmethod
      def from_path(cls, model_dir):
          config = configparser.RawConfigParser()
          result = config.read('config/common.cfg')
          print(f'read config result: {result}', flush=True) # empty
          print(f'config sections: {config.sections()}', flush=True) # empty
  
          subprocess.run(["ls", "-l"]) # don't see the config file or folder
  
          model_path = os.path.join(model_dir, "model.joblib")
          model = joblib.load(model_path)
  
          return cls(model, config)
  </code></pre>
  
  <p>Any suggestions on what I'm doing wrong or missing?</p>