code: def test_load_torch(self):
      torch_model = torchvision.models.resnet18()
      tmp_path = create_tmp_path() + ".pt"
      torch.save(torch_model, tmp_path, pickle_module=zoo_pickle_module)
      model = InferenceModel(10)
      model.load_torch(tmp_path)
      input_data = np.random.random([4, 3, 224, 224])
      output_data = model.predict(input_data)
      os.remove(tmp_path)
  
file_path: BigDL/python/orca/test/bigdl/orca/torch/test_inference_model_torch.py
imports: import os
  import pytest
  from unittest import TestCase
  from bigdl.orca.inference import InferenceModel
  from bigdl.orca.torch import zoo_pickle_module
  import torch
  import torchvision
  from bigdl.dllib.nncontext import *
label_desc: Use image node_id 3 for calling the TestInferenceModelTorch obj's underlying member method code with example usage: obj.test_load_torch() without return types