class_docstr: A testing suite that makes sure that the PeftModel class is correctly integrated into the transformers library.
class_docstr_tok: ["A","testing","suite","that","makes","sure","that","the","PeftModel","class","is","correctly","integrated","into","the","transformers","library","."]
docstr: Simple test that checks if the returned state dict of `get_adapter_state_dict()` method contains
  the expected keys.
docstr_tok: ["Simple","test","that","checks","if","the","returned","state","dict","of","`","get_adapter_state_dict","(",")","`","method","contains","the","expected","keys","."]
code: def test_peft_state_dict(self):
      """
      Simple test that checks if the returned state dict of `get_adapter_state_dict()` method contains
      the expected keys.
      """
      for model_id in self.peft_test_model_ids:
          for (
              transformers_class
          ) in self.transformers_test_model_classes:
              peft_model = transformers_class.from_pretrained(
                  model_id
              ).to(torch_device)
  
              state_dict = peft_model.get_adapter_state_dict()
  
              for key in state_dict.keys():
                  self.assertTrue("lora" in key)
  
imports: import os
  import tempfile
  import unittest
  from huggingface_hub import hf_hub_download
  from transformers import AutoModelForCausalLM, OPTForCausalLM
  from transformers.testing_utils import require_peft, require_torch, require_torch_gpu, slow, torch_device
  from transformers.utils import is_torch_available
label_desc: Use image node_id 3 for calling the PeftIntegrationTester obj's underlying member method code with example usage: obj.test_peft_state_dict() without return types