code: def test_logits_without_cache(
      self, test_name: str, model_type: str, padding, batch_size: int
  ):
      if batch_size == 1 and padding == "max_length":
          self.skipTest(
              "batch_size=1 + padding='max_length' is unsupported"
          )
  
      model_id = MODELS_DICT[model_type]
      self._test_logits(
          model_id,
          model_type=model_type,
          padding=padding,
          batch_size=batch_size,
      )
  
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 2 for calling the BetterTransformersDecoderTest obj's underlying member method code with example usage: obj.test_logits_without_cache(test_name, model_type, padding, batch_size) without return types