code: def gen_prototxt_from_caffemodel(self, data_path, input_shape):
      prototxt = "deploy.prototxt"
      data_injector = DataInjector(None, data_path)
      caffemodel = data_injector.caffemodel
      layers = caffemodel.layers or caffemodel.layer
      for item in layers:
          item.ClearField("blobs")
      with open(prototxt, "w") as f:
          f.write(str(caffemodel))
      return prototxt, data_injector
  
imports: from __future__ import unicode_literals
  from google.protobuf import text_format
  import numpy
  from mmdnn.conversion.caffe.graph import GraphBuilder, NodeKind, LAYER_IN_TRAIN_PROTO
  from mmdnn.conversion.caffe.mapper import NodeMapper, get_handler_name
  from mmdnn.conversion.caffe.resolver import get_caffe_resolver, has_pycaffe
  from mmdnn.conversion.caffe.errors import print_stderr, ConversionError
  from mmdnn.conversion.caffe.common_graph import Graph
  from mmdnn.conversion.caffe.utils import get_lower_case, get_upper_case
label_desc: Use image node_id 2 for calling the CaffeTransformer obj's underlying member method code with example usage: obj.gen_prototxt_from_caffemodel(data_path, input_shape) and returns: prototxt,  data_injector