class_docstr: Base class for job runners that use datasets.
class_docstr_tok: ["Base","class","for","job","runners","that","use","datasets","."]
code: def set_datasets_cache(
      self, cache_subdirectory: Optional[Path]
  ) -> None:
      datasets.config.HF_DATASETS_CACHE = cache_subdirectory
      logging.debug(
          f"datasets data cache set to: {datasets.config.HF_DATASETS_CACHE}"
      )
      datasets.config.DOWNLOADED_DATASETS_PATH = (
          datasets.config.HF_DATASETS_CACHE
          / datasets.config.DOWNLOADED_DATASETS_DIR
      )
      datasets.config.EXTRACTED_DATASETS_PATH = (
          datasets.config.HF_DATASETS_CACHE
          / datasets.config.EXTRACTED_DATASETS_DIR
      )
  
file_path: datasets-server/services/worker/src/worker/job_runners/_job_runner_with_datasets_cache.py
imports: import logging
  from pathlib import Path
  from typing import Optional
  import datasets.config
  from libcommon.utils import JobInfo
  from worker.config import AppConfig
  from worker.job_runners._job_runner_with_cache import JobRunnerWithCache
label_desc: Use image node_id 2 for calling the JobRunnerWithDatasetsCache obj's underlying member method code with example usage: obj.set_datasets_cache(cache_subdirectory) without return types