code: def test_huggingface_pytorch(
      sagemaker_session,
      gpu_instance_type,
      instance_count,
      huggingface_training_compiler_latest_version,
      huggingface_training_compiler_pytorch_latest_version,
      huggingface_dummy_dataset,
  ):
      """
      Test the HuggingFace estimator with PyTorch
      """
      with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
          data_path = os.path.join(DATA_DIR, "huggingface")
  
          hf = HuggingFace(
              py_version="py38",
              entry_point=os.path.join(data_path, "run_glue.py"),
              role="SageMakerRole",
              transformers_version=huggingface_training_compiler_latest_version,
              pytorch_version=huggingface_training_compiler_pytorch_latest_version,
              instance_count=instance_count,
              instance_type=gpu_instance_type,
              hyperparameters={
                  "model_name_or_path": "distilbert-base-cased",
                  "task_name": "wnli",
                  "do_train": True,
                  "do_eval": True,
                  "max_seq_length": 128,
                  "fp16": True,
                  "per_device_train_batch_size": 128,
                  "output_dir": "/opt/ml/model",
              },
              sagemaker_session=sagemaker_session,
              disable_profiler=True,
              compiler_config=HFTrainingCompilerConfig(),
              distribution={"pytorchxla": {"enabled": True}}
              if instance_count > 1
              else None,
          )
  
          hf.fit(huggingface_dummy_dataset)
  
imports: from __future__ import absolute_import
  import os
  from packaging import version
  import pytest
  from sagemaker.huggingface import HuggingFace
  from sagemaker.huggingface import TrainingCompilerConfig
  from sagemaker.tensorflow import TensorFlow
  from sagemaker.tensorflow import TrainingCompilerConfig
  from sagemaker.pytorch import PyTorch
  from sagemaker.pytorch import TrainingCompilerConfig
  from tests import integ
  from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
  from tests.integ.timeout import timeout
label_desc: Use image node_id 6 for calling a global function with example usage: test_huggingface_pytorch(sagemaker_session, gpu_instance_type, instance_count, huggingface_training_compiler_latest_version, huggingface_training_compiler_pytorch_latest_version, huggingface_dummy_dataset) without return types