code: def test_transform_with_repartition(self):
      # shards of pandas dataframe
      file_path = os.path.join(self.resource_path, "orca/data/csv")
      data_shard = bigdl.orca.data.pandas.read_csv(file_path)
      partitions = data_shard.rdd.glom().collect()
      for par in partitions:
          assert len(par) <= 1
  
      def negative(df, column_name):
          df[column_name] = df[column_name] * (-1)
          return df
  
      shard2 = data_shard.transform_shard(negative, "sale_price")
  
      shard3 = shard2.repartition(4)
      partitions3 = shard3.rdd.glom().collect()
      for par in partitions3:
          assert len(par) <= 1
  
      shard4 = shard2.repartition(1)
      partitions4 = shard4.rdd.glom().collect()
      for par in partitions4:
          assert len(par) <= 1
  
      shard5 = shard4.transform_shard(negative, "sale_price")
      partitions5 = shard5.rdd.glom().collect()
      for par in partitions5:
          assert len(par) <= 1
      # shards of list
      data = [
          [1, 2, 3, 4],
          [5, 6, 7, 8],
          [9, 10, 11, 12],
          [13, 14, 15, 16],
      ]
      sc = init_nncontext()
      rdd = sc.parallelize(data)
      data_shard = SparkXShards(rdd)
      shard2 = data_shard.repartition(6)
      partitions2 = shard2.rdd.glom().collect()
      for par in partitions2:
          assert len(par) <= 1
      shard3 = data_shard.repartition(1)
      partitions2 = shard3.rdd.glom().collect()
      for par in partitions2:
          assert len(par) <= 1
  
      # shards of numpy array
      data = [
          np.array([1, 2, 3, 4]),
          np.array([5, 6, 7, 8]),
          np.array([9, 10, 11, 12]),
          np.array([13, 14, 15, 16]),
      ]
      sc = init_nncontext()
      rdd = sc.parallelize(data)
      data_shard = SparkXShards(rdd)
      shard2 = data_shard.repartition(6)
      partitions2 = shard2.rdd.glom().collect()
      for par in partitions2:
          assert len(par) <= 1
      shard3 = data_shard.repartition(1)
      partitions2 = shard3.rdd.glom().collect()
      for par in partitions2:
          assert len(par) <= 1
  
imports: import os.path
  import pytest
  from unittest import TestCase
  import bigdl.orca.data
  import bigdl.orca.data.pandas
  from bigdl.orca.data import SharedValue
  from bigdl.dllib.nncontext import *
  from bigdl.orca.data.transformer import *
  from bigdl.orca import init_orca_context
label_desc: Use image node_id 12 for calling the TestSparkXShards obj's underlying member method code with example usage: obj.test_transform_with_repartition() and returns: df