code: def test_save_load_model(self, use_safetensors):
      accelerator = Accelerator()
      (
          model,
          optimizer,
          scheduler,
          train_dl,
          valid_dl,
      ) = create_components()
      accelerator.prepare(
          model, optimizer, scheduler, train_dl, valid_dl
      )
  
      model_signature = get_signature(model)
  
      with tempfile.TemporaryDirectory() as tmpdirname:
          accelerator.save_state(
              tmpdirname, safe_serialization=use_safetensors
          )
  
          # make sure random weights don't match
          load_random_weights(model)
          self.assertTrue(
              abs(model_signature - get_signature(model)) > 1e-3
          )
  
          # make sure loaded weights match
          accelerator.load_state(tmpdirname)
          self.assertTrue(
              abs(model_signature - get_signature(model)) < 1e-3
          )
  
imports: import json
  import os
  import pickle
  import tempfile
  from unittest.mock import patch
  import torch
  from parameterized import parameterized
  from torch.utils.data import DataLoader, TensorDataset
  from accelerate import DistributedType, infer_auto_device_map, init_empty_weights, load_checkpoint_and_dispatch
  from accelerate.accelerator import Accelerator
  from accelerate.state import GradientState, PartialState
  from accelerate.test_utils import require_bnb, require_multi_gpu, slow
  from accelerate.test_utils.testing import AccelerateTestCase, require_cuda
  from accelerate.utils import patch_environment
  from accelerate.utils.modeling import load_checkpoint_in_model
label_desc: Use image node_id 6 for calling the AcceleratorTester obj's underlying member method code with example usage: obj.test_save_load_model(use_safetensors) without return types