code: def __str__(self):
      def get_max_shape(data):
          if isinstance(data, dict):
              max = 0
              val = None
              for k, v in data.items():
                  tmp = reduce(lambda x, y: x * y, v.shape)
                  if tmp > max:
                      val = v.shape
                      max = tmp
              return val
          else:
              return data[0].shape
  
      hdr = "{:<20} {:<30} {:>20} {:>20}".format(
          "Type", "Name", "Param", "Output"
      )
      s = [hdr, "-" * 94]
      for node in self.topologically_sorted():
          data_shape = get_max_shape(node.data) if node.data else "--"
          out_shape = node.output_shape or "--"
          s.append(
              "{:<20} {:<30} {!s:>20} {!s:>20}".format(
                  node.kind, node.name, data_shape, tuple(out_shape)
              )
          )
      return "\n".join(s)
  
imports: from collections import namedtuple
  from functools import reduce
  from google.protobuf import text_format
  from copy import deepcopy
  import numbers
  import os
  import tempfile
  from mmdnn.conversion.caffe.mapper import get_handler_name
  from mmdnn.conversion.caffe.resolver import get_caffe_resolver, has_pycaffe
  from mmdnn.conversion.caffe.shape import *
  from mmdnn.conversion.caffe.errors import print_stderr, ConversionError
label_desc: Use image node_id 11 for calling the CaffeGraph obj's underlying member method code with example usage: obj.__str__() and returns: str, val, data