code: def _remove_ssa(cls, net, remap_dict):
      for op in net.op:
          for i, name in enumerate(op.output):
              if name in remap_dict:
                  op.output[i] = remap_dict[name]
      for i, out in enumerate(net.external_output):
          if out in remap_dict:
              net.external_output[i] = remap_dict[out]
  
imports: import collections
  import sys
  import zipfile
  import itertools
  import onnx.backend
  from caffe2.python import core, workspace, rnn_cell, gru_cell
  from caffe2.python.model_helper import ModelHelper
  from caffe2.proto import caffe2_pb2
  import caffe2.python.utils
  import numpy
  import onnx
  from onnx import TensorProto
  import onnx.numpy_helper
  import onnx.defs
  import onnx.shape_inference
  import onnx.utils
  from onnx.backend.base import Backend, Device, DeviceType, namedtupledict
  from caffe2.python.onnx.workspace import Workspace
  from caffe2.python.onnx.backend_rep import Caffe2Rep
  import caffe2.python._import_c_extension
  import warnings
label_desc: Use image node_id 8 for calling the Caffe2Backend obj's underlying member method code with example usage: obj._remove_ssa(cls, net, remap_dict) without return types