code: def test_prepare_default_dataset(tmp_path):
      df = prepare_default_dataset_causal_language_modeling(tmp_path)
      assert isinstance(df, pd.DataFrame)
      assert set(df.keys()) == set(
          ["instruction", "output", "id", "parent_id", "lang", "rank"]
      )
      assert df.shape == (8274, 6)
  
file_path: h2o-llmstudio/tests/src/datasets/test_text_causal_language_modeling_ds.py
imports: from unittest import mock
  from unittest.mock import MagicMock, patch
  import numpy
  import pandas
  import pytest
  from llm_studio.app_utils.default_datasets import prepare_default_dataset_causal_language_modeling
  from llm_studio.python_configs.text_causal_language_modeling_config import ConfigNLPCausalLMDataset, ConfigNLPCausalLMTokenizer, ConfigProblemBase
  from llm_studio.src.datasets.text_causal_language_modeling_ds import CustomDataset
label_desc: Use image node_id 1 for calling a global function with example usage: test_prepare_default_dataset(tmp_path) without return types