code: def create_auto_shard_datasets(config, batch_size):
      import tensorflow as tf
  
      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 shutil
  from unittest import TestCase
  import numpy
  import pytest
  import tensorflow
  from zoo import init_nncontext
  from zoo.orca.data import XShards
  import zoo.orca.data.pandas
  from zoo.orca.learn.tf2 import Estimator
  from zoo.ray import RayContext
  import ray
  import os
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