code: def test_generation_post_attn_layer_norm(self):
      model_id = "facebook/opt-350m"
  
      EXPECTED_OUTPUTS = [
          "Today is a beautiful day and I want to",
          "In the city of San Francisco, the city",
          "Paris is the capital of France and the capital",
          "Computers and mobile phones have taken over the",
      ]
  
      predicted_outputs = []
      tokenizer = GPT2Tokenizer.from_pretrained(model_id)
      model = OPTForCausalLM.from_pretrained(model_id)
  
      for prompt in self.prompts:
          input_ids = tokenizer(prompt, return_tensors="pt").input_ids
  
          generated_ids = model.generate(input_ids, max_length=10)
  
          generated_string = tokenizer.batch_decode(
              generated_ids, skip_special_tokens=True
          )
          predicted_outputs += generated_string
  
      self.assertListEqual(predicted_outputs, EXPECTED_OUTPUTS)
  
imports: import copy
  import tempfile
  import unittest
  import timeout_decorator
  from transformers import OPTConfig, is_torch_available
  from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
label_desc: Use image node_id 4 for calling the OPTGenerationTest obj's underlying member method code with example usage: obj.test_generation_post_attn_layer_norm() without return types