code: def is_compatible(cls, model, device="CPU", **kwargs):
      if hasattr(
          super(Caffe2Backend, cls), "is_compatible"
      ) and callable(super(Caffe2Backend, cls).is_compatible):
          if not super(Caffe2Backend, cls).is_compatible(
              model, device, **kwargs
          ):
              return False
      # TODO: should have an unspported list of operators, be optimistic for now
      return True
  
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 26 for calling the Caffe2Backend obj's underlying member method code with example usage: obj.is_compatible(cls, model, device) and returns: True, False