code: def test_load_state_dic(self):
      wrapper = BaalTransformersTrainer(
          model=self.model,
          args=self.args,
          train_dataset=self.dataset,
          eval_dataset=self.dataset,
          tokenizer=None,
      )
      model_weights = deepcopy(list(wrapper.model.parameters())[0])
      initial_state_dict = deepcopy(wrapper.model.state_dict())
      wrapper.train()
      weights_after_training = deepcopy(
          list(wrapper.model.parameters())[0]
      )
      assert not torch.equal(
          model_weights.data, weights_after_training.data
      )
  
      wrapper.load_state_dict(initial_state_dict)
  
      reloaded_weights = deepcopy(list(wrapper.model.parameters())[0])
      assert torch.equal(model_weights.data, reloaded_weights.data)
  
file_path: baal/tests/transformers_trainer_wrapper_test.py
imports: import unittest
  from copy import deepcopy
  import numpy
  import pytest
  import torch
  from transformers import GPT2LMHeadModel, GPT2Config
  from transformers import TrainingArguments
  from baal.transformers_trainer_wrapper import BaalTransformersTrainer
label_desc: Use image node_id 3 for calling the BaalTransformerTrainer obj's underlying member method code with example usage: obj.test_load_state_dic() without return types