class_docstr: A `SparkDatasetConverter` object holds one materialized spark dataframe and
  can be used to make one or more tensorflow datasets or torch dataloaders.
  The `SparkDatasetConverter` object is picklable and can be used in remote
  processes.
  See `make_spark_converter`
class_docstr_tok: ["A","`","SparkDatasetConverter","`","object","holds","one","materialized","spark","dataframe","and","can","be","used","to","make","one","or","more","tensorflow","datasets","or","torch","dataloaders",".","The","`","SparkDatasetConverter","`","object","is","picklable","and","can","be","used","in","remote","processes",".","See","`","make_spark_converter","`"]
code: def _check_and_set_overriden_petastorm_args(
      petastorm_reader_kwargs, num_epochs, workers_count
  ):
      # override some arguments default values of petastorm reader
      petastorm_reader_kwargs["num_epochs"] = num_epochs
      if workers_count is None:
          # TODO: generate a best tuned value for default worker count value
          workers_count = 4
      petastorm_reader_kwargs["workers_count"] = workers_count
      _check_rank_and_size_consistent_with_horovod(
          petastorm_reader_kwargs
      )
  
imports: import atexit
  import datetime
  import logging
  import os
  import shutil
  import threading
  import time
  import uuid
  from distutils.version import LooseVersion
  from multiprocessing.pool import ThreadPool
  from typing import List, Any
  import pyspark
  from pyarrow import LocalFileSystem
  from pyspark.sql.session import SparkSession
  from pyspark.sql.types import ArrayType, DoubleType, FloatType
  from six.moves.urllib.parse import urlparse
  from petastorm import make_batch_reader
  from petastorm.fs_utils import FilesystemResolver, get_filesystem_and_path_or_paths, normalize_dir_url
  from fsspec.core import strip_protocol
label_desc: Use image node_id 3 for calling the SparkDatasetConverter obj's underlying member method code with example usage: obj._check_and_set_overriden_petastorm_args(petastorm_reader_kwargs, num_epochs, workers_count) without return types