code: def c2_native_run_op(op_def, inputs):
      ws = Workspace()
      if isinstance(inputs, dict):
          for key, value in inputs.items():
              ws.FeedBlob(key, value, op_def.device_option)
      else:
          assert len(op_def.input) == len(inputs)
          for key, value in zip(op_def.input, inputs):
              ws.FeedBlob(key, value, op_def.device_option)
  
      ws.RunOperatorOnce(op_def)
  
      output_names = op_def.output
      output_values = [ws.FetchBlob(name) for name in output_names]
      return ws, namedtupledict("Outputs", output_names)(*output_values)
  
file_path: pytorch/caffe2/python/onnx/helper.py
imports: from caffe2.proto import caffe2_pb2
  from onnx.backend.base import namedtupledict
  from caffe2.python.onnx.workspace import Workspace
  import logging
  import time
label_desc: Use image node_id 1 for calling a global function with example usage: c2_native_run_op(op_def, inputs) and returns: ws,  namedtupledict