code: def test_language_modeling(self):
      subprocess.run(
          "cp ../examples/onnxruntime/training/question-answering/run_qa.py ./",
          shell=True,
      )
  
      subprocess.run(
          "torchrun"
          " --nproc_per_node=1"
          " run_clm.py"
          " --model_name_or_path gpt2"
          " --do_train"
          " --do_eval"
          " --dataset_name wikitext"
          " --dataset_config_name wikitext-2-raw-v1"
          " --max_train_samples 30"
          " --output_dir /tmp/gpt2"
          " --overwrite_output_dir"
          " --max_steps 50"
          " --logging_steps 50"
          " --per_device_train_batch_size 2"
          " --per_device_eval_batch_size 2"
          " --fp16 --optim adamw_ort_fused",
          shell=True,
          check=True,
      )
  
file_path: optimum/tests/onnxruntime/training/nightly_test_examples.py
imports: import subprocess
  import unittest
  import pytest
  from transformers.testing_utils import slow
label_desc: Use image node_id 7 for calling the ORTTrainerExampleTest obj's underlying member method code with example usage: obj.test_language_modeling() without return types