code: def __call__(self, name, inputs, outputs):
      dumped_list = _dump_graph(outputs)
      f = None
      net = None
      if self.caffemodel is not None:
          net = caffe_pb.NetParameter()
      try:
          if self.prototxt is not None:
              f = open(self.prototxt, "wt")
              f.write('name: "{}"\n'.format(name))
              assert len(inputs) == 1
              f.write(
                  "layer {\n"
                  '  name: "data"\n'
                  '  type: "Input"\n'
                  '  top: "data"\n'
                  "  input_param { shape: {"
              )
              for i in inputs[0].shape:
                  f.write(" dim: " + str(i))
              f.write(" } }\n" "}\n")
          for i in dumped_list:
              self.dump_function_object(i, f, net)
      finally:
          if f is not None:
              f.close()
  
      if net is not None:
          with open(self.caffemodel, "wb") as f:
              f.write(net.SerializeToString())
          if self.debug:
              import google.protobuf.text_format
  
              with open(self.caffemodel + ".txt", "w") as f:
                  f.write(
                      google.protobuf.text_format.MessageToString(net)
                  )
  
imports: import collections
  import heapq
  import os
  import numpy
  import six
  import chainer
  from chainer import function
  from chainer import function_node
  from chainer.links.caffe.protobuf3 import caffe_pb2
  from chainer import variable
label_desc: Use image node_id 6 for calling the _RetrieveAsCaffeModel obj's underlying member method code with example usage: obj.__call__(name, inputs, outputs) without return types