code: def _test_state_dict_before_forward(cls, config, rank, group):
      ddp_model = cls.get_wrapped_model(
          group, cuda_first=False, config=config
      )
      sd = ddp_model.state_dict()
      for param_name in ("embed_tokens.weight", "vocab_bias"):
          wt = sd[param_name]
          assert (
              wt.dtype == torch.float32
          ), f"got dtype {wt.dtype} for {param_name}, expected torch.float32"
      cls._train_for_several_steps(
          ddp_model, 1, ddp_model.mixed_precision
      )
  
imports: import functools
  import unittest
  from parameterized import parameterized
  import pytest
  import torch
  from torch import nn
  from fairscale.fair_dev.testing.testing import dist_init, objects_are_equal, skip_if_cuda, teardown, temp_files_ctx
  from fairscale.internal import torch_version
  from fairscale.nn.data_parallel import FullyShardedDataParallel
  from .test_fsdp import CONFIG_OPTIONS, DistributedTest, NestedWrappedModule, TransformerWithSharedParams, rename_test, spawn_and_init
label_desc: Use image node_id 5 for calling the TestSaveLoadStateDict obj's underlying member method code with example usage: obj._test_state_dict_before_forward(cls, config, rank, group) without return types