code: def load_caffe(model_desc, model_file):
      """
      Load a caffe model. You must be able to ``import caffe`` to use this
      function.
  
      Args:
          model_desc (str): path to caffe model description file (.prototxt).
          model_file (str): path to caffe model parameter file (.caffemodel).
      Returns:
          dict: the parameters.
      """
      with change_env("GLOG_minloglevel", "2"):
          import caffe
  
          caffe.set_mode_cpu()
          net = caffe.Net(model_desc, model_file, caffe.TEST)
      param_dict = CaffeLayerProcessor(net).process()
      logger.info(
          "Model loaded from caffe. Params: "
          + ", ".join(sorted(param_dict.keys()))
      )
      return 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 1 for calling a global function with example usage: load_caffe(model_desc, model_file) and returns: param_dict