code: def generate_test_output_data(
      caffe2_init_net, caffe2_predict_net, inputs
  ):
      p = c2_workspace.Predictor(caffe2_init_net, caffe2_predict_net)
      inputs_map = {input[0]: input[1] for input in inputs}
  
      output = p.run(inputs_map)
      c2_workspace.ResetWorkspace()
      return output
  
imports: import argparse
  import glob
  import json
  import os
  import shutil
  import tarfile
  import tempfile
  from urllib.request import urlretrieve
  import boto3
  import caffe2.python.onnx.backend
  import caffe2.python.onnx.frontend
  import caffe2.python.workspace
  import numpy
  import onnx
  import onnx.backend
  from caffe2.proto import caffe2_pb2
  from caffe2.python.models.download import deleteDirectory, downloadFromURLToFile, getURLFromName
  from onnx import numpy_helper
label_desc: Use image node_id 7 for calling a global function with example usage: generate_test_output_data(caffe2_init_net, caffe2_predict_net, inputs) and returns: output