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 tests the basic usage of PEFT model through `from_pretrained`. This test tests if
  add_adapter works as expected with a state_dict being passed.
docstr_tok: ["Simple","test","that","tests","the","basic","usage","of","PEFT","model","through","`","from_pretrained","`",".","This","test","tests","if","add_adapter","works","as","expected","with","a","state_dict","being","passed","."]
code: def test_peft_add_adapter_with_state_dict(self):
      """
      Simple test that tests the basic usage of PEFT model through `from_pretrained`. This test tests if
      add_adapter works as expected with a state_dict being passed.
      """
      from peft import LoraConfig
  
      dummy_input = torch.LongTensor([[0, 1, 2, 3, 4, 5, 6, 7]]).to(
          torch_device
      )
  
      for model_id, peft_model_id in zip(
          self.transformers_test_model_ids, self.peft_test_model_ids
      ):
          for (
              transformers_class
          ) in self.transformers_test_model_classes:
              model = transformers_class.from_pretrained(model_id).to(
                  torch_device
              )
  
              peft_config = LoraConfig(init_lora_weights=False)
  
              with self.assertRaises(ValueError):
                  model.load_adapter(peft_model_id=None)
  
              state_dict_path = hf_hub_download(
                  peft_model_id, "adapter_model.bin"
              )
  
              dummy_state_dict = torch.load(state_dict_path)
  
              model.load_adapter(
                  adapter_state_dict=dummy_state_dict,
                  peft_config=peft_config,
              )
              with self.assertRaises(ValueError):
                  model.load_adapter(
                      model.load_adapter(
                          adapter_state_dict=dummy_state_dict,
                          peft_config=None,
                      )
                  )
              self.assertTrue(
                  self._check_lora_correctly_converted(model)
              )
  
              # dummy generation
              _ = model.generate(input_ids=dummy_input)
  
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 15 for calling the PeftIntegrationTester obj's underlying member method code with example usage: obj.test_peft_add_adapter_with_state_dict() without return types