code: def create_auto_shard_datasets(config, batch_size):
      data_path = os.path.join(
          resource_path, "orca/learn/test_auto_shard/*.csv"
      )
      dataset = tf.data.Dataset.list_files(data_path)
      dataset = dataset.interleave(lambda x: tf.data.TextLineDataset(x))
      dataset = dataset.map(lambda x: tf.strings.to_number(x))
      dataset = dataset.map(lambda x: (x, x))
      dataset = dataset.batch(batch_size)
      return dataset
  
imports: import math
  import os
  import shutil
  import tempfile
  import pytest
  from unittest import TestCase
  import tensorflow
  import numpy
  from bigdl.orca.data.pandas import read_csv
  from bigdl.orca.data import SparkXShards, XShards
  from bigdl.orca.data.tf.data import Dataset
  from bigdl.orca.learn.tf2 import Estimator
  from bigdl.orca.ray import OrcaRayContext
  from bigdl.orca import OrcaContext
label_desc: Use image node_id 8 for calling a global function with example usage: create_auto_shard_datasets(config, batch_size) and returns: dataset