code: def process(self):
      for idx, layer in enumerate(self.net.layers):
          param = layer.blobs
          name = self.layer_names[idx]
          if layer.type in self.processors:
              logger.info(
                  "Processing layer {} of type {}".format(
                      name, layer.type
                  )
              )
              dic = self.processors[layer.type](idx, name, param)
              self.param_dict.update(dic)
          elif len(layer.blobs) != 0:
              logger.warn(
                  "{} layer contains parameters but is not supported!".format(
                      layer.type
                  )
              )
      return self.param_dict
  
file_path: tensorpack/tensorpack/utils/loadcaffe.py
imports: import numpy
  import os
  import sys
  from .None import logger
  from .concurrency import subproc_call
  from .fs import download, get_dataset_path
  from .utils import change_env
label_desc: Use image node_id 2 for calling the CaffeLayerProcessor obj's underlying member method code with example usage: obj.process() and returns: self