code: def test_pickle(self, device, dtype, module_info, training):
      # Test that module can be pickled and unpickled.
      module_cls = module_info.module_cls
      module_inputs = module_info.module_inputs_func(
          module_info,
          device=device,
          dtype=dtype,
          requires_grad=False,
          training=training,
      )
      for module_input in module_inputs:
          if module_input.forward_input is None:
              continue
  
          args, kwargs = (
              module_input.constructor_input.args,
              module_input.constructor_input.kwargs,
          )
  
          with freeze_rng_state():
              # === Instantiate the module. ===
              args, kwargs = (
                  module_input.constructor_input.args,
                  module_input.constructor_input.kwargs,
              )
              m = module_cls(*args, **kwargs)
              m.to(device).to(dtype)
              m.train(training)
  
              # === Do forward pass. ===
              args, kwargs = (
                  module_input.forward_input.args,
                  module_input.forward_input.kwargs,
              )
              output = m(*args, **kwargs)
  
              # === Check unpickled module gives the same output. ===
              with tempfile.TemporaryFile() as f:
                  torch.save(m, f)
                  f.seek(0)
                  m_copy = torch.load(f)
                  output_from_copy = m_copy(*args, **kwargs)
                  self.assertEqual(output, output_from_copy)
  
imports: from itertools import chain, product
  from inspect import signature, isgenerator
  from copy import deepcopy
  import tempfile
  from operator import methodcaller
  import torch
  from torch._subclasses.meta_utils import assert_metadata_eq
  from torch.testing._internal.common_cuda import with_tf32_off
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, onlyCUDA, toleranceOverride, tol, skipMeta
  from torch.testing._internal.common_modules import module_db, modules, ModuleErrorEnum, TrainEvalMode
  from torch.testing._internal.common_utils import TestCase, run_tests, freeze_rng_state, mock_wrapper, get_tensors_from, gradcheck, gradgradcheck
  from unittest.mock import patch, call
label_desc: Use image node_id 6 for calling the TestModule obj's underlying member method code with example usage: obj.test_pickle(device, dtype, module_info, training) without return types