code: def test_opt():
      MODEL_LIST = [
          transformers.OPTModel,
          transformers.OPTForCausalLM,
      ]
  
      config = transformers.OPTConfig(
          vocab_size=100,
          hidden_size=128,
          num_hidden_layers=4,
          num_attention_heads=4,
      )
  
      def data_gen():
          input_ids = torch.zeros(
              (BATCH_SIZE, SEQ_LENGHT), dtype=torch.int64
          )
          attention_mask = torch.zeros(
              (BATCH_SIZE, SEQ_LENGHT), dtype=torch.int64
          )
          kwargs = dict(
              input_ids=input_ids, attention_mask=attention_mask
          )
          return kwargs
  
      for model_cls in MODEL_LIST:
          model = model_cls(config=config)
          split_model_and_compare_output(model, data_gen)
  
imports: import pytest
  import torch
  import transformers
  from hf_utils import split_model_and_compare_output
label_desc: Use image node_id 1 for calling a global function with example usage: test_opt() and returns: kwargs