code: def test_make_spark_convert_from_saved_df_path(spark_test_ctx):
      df1 = spark_test_ctx.spark.range(100, 101)
      output_path = os.path.join(
          spark_test_ctx.tempdir,
          "test_make_spark_convert_from_saved_df_path",
      )
      df1.write.parquet("file:" + output_path)
      converter1 = make_spark_converter(output_path)
  
      def map_fn(_):
          with converter1.make_torch_dataloader(
              num_epochs=1
          ) as dataloader:
              for batch in dataloader:
                  ret = batch["id"][0]
          return ret
  
      result = (
          spark_test_ctx.spark.sparkContext.parallelize(range(1), 1)
          .map(map_fn)
          .collect()[0]
      )
      assert result == 100
  
imports: import os
  import subprocess
  import sys
  import tempfile
  import threading
  import time
  from distutils.version import LooseVersion
  import numpy
  import pyspark
  import pytest
  import py4j
  import tensorflow.compat.v1
  from pyspark.sql.functions import pandas_udf
  from pyspark.sql.types import ArrayType, BinaryType, BooleanType, ByteType, DoubleType, FloatType, IntegerType, LongType, ShortType, StringType, StructField, StructType
  from six.moves.urllib.parse import urlparse
  from petastorm import make_batch_reader
  from petastorm.fs_utils import FilesystemResolver
  from petastorm.spark import SparkDatasetConverter, make_spark_converter, spark_dataset_converter
  from petastorm.spark.spark_dataset_converter import _check_dataset_file_median_size, _check_parent_cache_dir_url, _check_rank_and_size_consistent_with_horovod, _check_url, _get_horovod_rank_and_size, _get_spark_session, _make_sub_dir_url, register_delete_dir_handler, _wait_file_available, _normalize_databricks_dbfs_url
  from unittest import mock
  from petastorm.tests.test_tf_utils import create_tf_graph
label_desc: Use image node_id 30 for calling a global function with example usage: test_make_spark_convert_from_saved_df_path(spark_test_ctx) and returns: ret