code: def dataset(self, tokenizer=None):
      # setup tokenizer
      if tokenizer is None:
          tokenizer = AutoTokenizer.from_pretrained(
              self.tokenizer_name, use_fast=False
          )
          if tokenizer.pad_token is None:
              tokenizer.pad_token = tokenizer.eos_token
      data_args = GlueDataTrainingArguments(
          task_name="mrpc",
          data_dir="./hf_transformers/tests/fixtures/tests_samples/MRPC",
          overwrite_cache=True,
      )
      return GlueDataset(data_args, tokenizer=tokenizer, mode="train")
  
imports: import random
  import datasets
  import torch
  import adapters
  from adapters import AutoAdapterModel
  from transformers import AutoFeatureExtractor, AutoTokenizer, GlueDataset, GlueDataTrainingArguments
  from transformers.testing_utils import torch_device
label_desc: Use image node_id 4 for calling the AdapterTestBase obj's underlying member method code with example usage: obj.dataset(tokenizer) and returns: GlueDataset