code: def test_optimize_model(Model, Tokenizer, model_path, prompt):
      tokenizer = Tokenizer.from_pretrained(
          model_path, trust_remote_code=True
      )
      input_ids = tokenizer.encode(prompt, return_tensors="pt")
  
      model = Model.from_pretrained(
          model_path,
          load_in_4bit=True,
          optimize_model=False,
          trust_remote_code=True,
      )
      logits_base_model = (model(input_ids)).logits
  
      model = Model.from_pretrained(
          model_path,
          load_in_4bit=True,
          optimize_model=True,
          trust_remote_code=True,
      )
      logits_optimized_model = (model(input_ids)).logits
      diff = abs(logits_base_model - logits_optimized_model).flatten()
  
      assert any(diff) is False
  
imports: import os
  import pytest
  from bigdl.llm.transformers import AutoModelForCausalLM, AutoModel
  from transformers import LlamaTokenizer, AutoTokenizer
label_desc: Use image node_id 1 for calling a global function with example usage: test_optimize_model(Model, Tokenizer, model_path, prompt) without return types