code: def _validate_cache_dir(self):
      # Define this so that we don't reference self in create_cache_and_write_probe, which will result in a pickling
      # error due to pickling the SparkContext.
      cache_dir = self._cache_dir
  
      # Returns the path of the created file.
      def create_cache_and_write_probe(context):
          # makedirs with exist_ok will recursively create the directory. It will not throw an error if directories
          # already exist.
          os.makedirs(cache_dir, exist_ok=True)
          probe_file = os.path.join(
              cache_dir, "fs_test" + uuid.uuid4().hex
          )
          # Opening the file in append mode will create a new file unless it already exists, in which case it will not
          # change the file contents.
          open(probe_file, "a")
          return [probe_file]
  
      if self._spark.conf.get("spark.master", "").startswith("local"):
          return
  
      # If the cluster is multi-node, make sure that the user provided a cache_dir and that it is on an NFS
      # accessible to the driver.
      # TODO: Stream batches to the driver using ArrowCollectSerializer instead of throwing an error.
      if self._cache_dir:
          probe = (
              self._spark.sparkContext.parallelize(range(1), 1)
              .mapPartitions(create_cache_and_write_probe)
              .collect()
          )
          if os.path.isfile(probe[0]):
              return
  
      raise ValueError(
          "When using Dataset.from_spark on a multi-node cluster, the driver and all workers should be able to access cache_dir"
      )
  
imports: import os
  import posixpath
  import uuid
  from dataclasses import dataclass
  from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
  import numpy
  import pyarrow
  import datasets
  from datasets.arrow_writer import ArrowWriter, ParquetWriter
  from datasets.config import MAX_SHARD_SIZE
  from datasets.filesystems import is_remote_filesystem, rename
  from datasets.iterable_dataset import _BaseExamplesIterable
  from datasets.utils.py_utils import convert_file_size_to_int
label_desc: Use image node_id 2 for calling the Spark obj's underlying member method code with example usage: obj._validate_cache_dir() and returns: list