class_docstr: A wrapper around the traced model in Caffe2's protobuf format.
  The exported graph has different inputs/outputs from the original Pytorch
  model, as explained in :class:`Caffe2Tracer`. This class wraps around the
  exported graph to simulate the same interface as the original Pytorch model.
  It also provides functions to save/load models in Caffe2's format.'
  
  Examples:
  ::
      c2_model = Caffe2Tracer(cfg, torch_model, inputs).export_caffe2()
      inputs = [{"image": img_tensor_CHW}]
      outputs = c2_model(inputs)
      orig_outputs = torch_model(inputs)
docstr: caffe2.core.Net: the underlying caffe2 predict net
docstr_tok: ["caffe2.core.Net",":","the","underlying","caffe2","predict","net"]
code: def predict_net(self):
      """
      caffe2.core.Net: the underlying caffe2 predict net
      """
      return self._predict_net
  
imports: import copy
  import logging
  import os
  import torch
  from caffe2.proto import caffe2_pb2
  from torch import nn
  from detectron2.config import CfgNode
  from detectron2.utils.file_io import PathManager
  from .caffe2_inference import ProtobufDetectionModel
  from .caffe2_modeling import META_ARCH_CAFFE2_EXPORT_TYPE_MAP, convert_batched_inputs_to_c2_format
  from .shared import get_pb_arg_vali, get_pb_arg_vals, save_graph
label_desc: Use image node_id 2 for calling the Caffe2Model obj's underlying member method code with example usage: obj.predict_net() and returns: self