code: def _parse_config(self, config):
          
          self._batch_size = config['batch_size']
          self._im_height = config['im_height']
          self._im_width = config['im_width']
          self._num_channels = config['channels']
          self._output_layer = config['out_layer']
          self._feature_layer = config['feature_layer']
          self._out_size = None
          if 'out_size' in config.keys():
              self._out_size = config['out_size']
          self._input_arr = np.zeros([self._batch_size, self._im_height,
                                      self._im_width, self._num_channels])
  
          if self._model_dir is None:
              self._net_data = np.load(config['caffe_weights']).item()
              self._mean = np.load(config['mean_file'])
              self._model_filename = None
          else:
              self._net_data = None
              self._mean = np.load(os.path.join(self._model_dir, 'mean.npy'))
              self._model_filename = os.path.join(self._model_dir, 'model.ckpt')
docs: Parses a tensorflow configuration