code: def test_generation(
      self,
      test_name: str,
      model_type: str,
      batch_size: int,
      padding: str,
  ):
      if batch_size == 1 and padding == "max_length":
          self.skipTest(
              "batch_size=1 + padding='max_length' is unsupported"
          )
  
      model_id = MODELS_DICT[model_type]
      tokenizer = AutoTokenizer.from_pretrained(model_id)
  
      model = AutoModelForCausalLM.from_pretrained(model_id)
  
      if (
          not hasattr(tokenizer, "pad_token")
          or tokenizer.pad_token is None
      ):
          if tokenizer.eos_token != "":
              tokenizer.pad_token = tokenizer.eos_token
          else:
              tokenizer.pad_token = "w"
  
      text = ["This is me and me"]
      if batch_size > 1:
          text.append("Please continue this my dear me")
      inp = tokenizer(
          text, return_tensors="pt", padding=padding, max_length=30
      )
  
      length = 50
      result_vanilla = model.generate(
          **inp, num_beams=1, min_length=length, max_length=length
      )
  
      model = BetterTransformer.transform(model)
  
      result_bettertransformer = model.generate(
          **inp, num_beams=1, min_length=length, max_length=length
      )
  
      self.assertTrue(
          torch.allclose(result_vanilla, result_bettertransformer),
          f" Maxdiff: {(result_vanilla - result_bettertransformer).abs().max()}",
      )
  
imports: import gc
  import unittest
  import pytest
  import torch
  from parameterized import parameterized
  from testing_utils import MODELS_DICT, BetterTransformersTestMixin
  from transformers import AutoModelForCausalLM, AutoTokenizer
  from optimum.bettertransformer import BetterTransformer
  from optimum.utils import BloomDummyPastKeyValuesGenerator, DummyPastKeyValuesGenerator, NormalizedConfigManager
  from optimum.utils.testing_utils import grid_parameters, require_accelerate, require_torch_gpu
label_desc: Use image node_id 6 for calling the BetterTransformersDecoderTest obj's underlying member method code with example usage: obj.test_generation(test_name, model_type, batch_size, padding) without return types