code: def execute_hook(
      self, config, torchscript_folder, torchscript_hook
  ) -> None:
      task = build_task(config)
      task.prepare()
  
      # create checkpoint dir, verify on_start hook runs
      os.mkdir(torchscript_folder)
      torchscript_hook.on_start(task)
  
      task.train = True
      # call the on end function
      torchscript_hook.on_end(task)
  
      # load torchscript file
      torchscript_file_name = (
          f"{torchscript_hook.torchscript_folder}/{TORCHSCRIPT_FILE}"
      )
      torchscript = torch.jit.load(torchscript_file_name)
      # compare model load from checkpoint vs torchscript
      with torch.no_grad():
          batchsize = 1
          model = task.model
          input_data = torch.randn(
              (batchsize,) + model.input_shape, dtype=torch.float
          )
          if torch.cuda.is_available():
              input_data = input_data.cuda()
              model = model.cuda()
              torchscript = torchscript.cuda()
          checkpoint_out = model(input_data)
          torchscript_out = torchscript(input_data)
          self.assertTrue(
              torch.allclose(checkpoint_out, torchscript_out, atol=1e-5)
          )
  
file_path: ClassyVision/test/hooks_torchscript_hook_test.py
imports: import copy
  import os
  import shutil
  import tempfile
  import torch
  from classy_vision.hooks import TorchscriptHook
  from classy_vision.models import ResNet
  from classy_vision.tasks import build_task
  from test.generic.config_utils import get_test_task_config
  from test.generic.hook_test_utils import HookTestBase
label_desc: Use image node_id 4 for calling the TestTorchscriptHook obj's underlying member method code with example usage: obj.execute_hook(config, torchscript_folder, torchscript_hook) without return types