class_docstr: Test data
class_docstr_tok: ["Test","data"]
code: def test_dataset(self, dataset):
      train_dataset = get_dataset(
          dataset,
          self.tokenizer,
          nsamples=self.NBSAMPLES,
          seqlen=self.SEQLEN,
          split="train",
      )
      self.assertEqual(len(train_dataset), self.NBSAMPLES)
      self.assertCountEqual(
          list(train_dataset[0].keys()), ["input_ids", "attention_mask"]
      )
      self.assertEqual(
          list(train_dataset[0]["input_ids"].size()), [1, self.SEQLEN]
      )
  
imports: import tempfile
  import unittest
  import torch
  from parameterized import parameterized
  from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer
  from transformers.testing_utils import slow
  from optimum.gptq import GPTQQuantizer, load_quantized_model
  from optimum.gptq.data import get_dataset
  from optimum.utils.import_utils import is_auto_gptq_available
  from optimum.utils.testing_utils import require_accelerate, require_auto_gptq, require_torch_gpu
label_desc: Use image node_id 2 for calling the GPTQDataTest obj's underlying member method code with example usage: obj.test_dataset(dataset) without return types