docstr: Test reassigning attributes to a different type
docstr_tok: ["Test","reassigning","attributes","to","a","different","type"]
code: def test_reassigning_attributes(self) -> None:
      """
      Test reassigning attributes to a different type
      """
  
      my_unit = Dummy()
  
      # create new objects
      module_e = nn.Linear(1, 1)
      loss_fn_f = nn.CrossEntropyLoss()
      optimizer_g = torch.optim.SGD(module_e.parameters(), lr=0.1)
      lr_scheduler_h = torch.optim.lr_scheduler.StepLR(
          optimizer_g, step_size=30, gamma=0.1
      )
  
      # reassigning module_a to be an optimizer should work
      self.assertTrue("module_a" in my_unit.tracked_modules())
      # pyre-fixme[8]: Attribute has type `Linear`; used as `SGD`.
      my_unit.module_a = optimizer_g
      self.assertTrue("module_a" not in my_unit.tracked_modules())
      self.assertTrue("module_a" in my_unit.tracked_optimizers())
  
      # reassigning optimizer_c to be an lr_scheduler should work
      self.assertTrue("optimizer_c" in my_unit.tracked_optimizers())
      # pyre-fixme[8]: Attribute has type `SGD`; used as `StepLR`.
      my_unit.optimizer_c = lr_scheduler_h
      self.assertTrue("optimizer_c" not in my_unit.tracked_optimizers())
      self.assertTrue("optimizer_c" in my_unit.tracked_lr_schedulers())
  
      # reassigning lr_scheduler_d to be a nn.module should work
      self.assertTrue(
          "lr_scheduler_d" in my_unit.tracked_lr_schedulers()
      )
      # pyre-fixme[8]: Attribute has type `StepLR`; used as `CrossEntropyLoss`.
      my_unit.lr_scheduler_d = loss_fn_f
      self.assertTrue(
          "lr_scheduler_d" not in my_unit.tracked_lr_schedulers()
      )
      self.assertTrue("lr_scheduler_d" in my_unit.tracked_modules())
  
      self.assertTrue(
          "grad_scaler_e" in my_unit.tracked_misc_statefuls()
      )
      # pyre-fixme[8]: Attribute has type `GradScaler`; used as `CrossEntropyLoss`.
      my_unit.grad_scaler_e = loss_fn_f
      self.assertTrue(
          "grad_scaler_e" not in my_unit.tracked_misc_statefuls()
      )
      self.assertTrue("grad_scaler_e" in my_unit.tracked_modules())
  
imports: import unittest
  from typing import Any, Dict
  from unittest.mock import patch
  import torch
  from torch import nn
  from torchtnt.framework._test_utils import DummyAutoUnit
  from torchtnt.framework.unit import AppStateMixin
  from torchtnt.utils.env import init_from_env
  from torchtnt.utils.lr_scheduler import TLRScheduler
  from torchtnt.utils.prepare_module import FSDPOptimizerWrapper
label_desc: Use image node_id 6 for calling the AppStateMixinTest obj's underlying member method code with example usage: obj.test_reassigning_attributes() without return types