code: def setUp(self):
      self.causal_lm_model_id = (
          "trl-internal-testing/tiny-random-GPTNeoXForCausalLM"
      )
      self.seq_to_seq_model_id = (
          "trl-internal-testing/tiny-random-T5ForConditionalGeneration"
      )
  
      if is_peft_available():
          from peft import LoraConfig, get_peft_model
  
          lora_config = LoraConfig(
              r=16,
              lora_alpha=32,
              lora_dropout=0.05,
              bias="none",
              task_type="CAUSAL_LM",
          )
  
          causal_lm_model = AutoModelForCausalLM.from_pretrained(
              self.causal_lm_model_id
          )
          self.peft_model = get_peft_model(causal_lm_model, lora_config)
  
file_path: trl/tests/test_no_peft.py
imports: import sys
  import unittest
  from unittest.mock import patch
  import torch
  from transformers import AutoModelForCausalLM, AutoTokenizer
  from .testing_utils import is_peft_available, require_peft
label_desc: Use image node_id 1 for calling the TestPeftDependancy obj's underlying member method code with example usage: obj.setUp() without return types