class_docstr: Creates a `Dataset` that includes only 1/`num_shards` of this dataset.
  The Dataset will contain all elements of total dataset whose index % num_shards = rank.
code: def _load_data(self, schema):
      if self.num_shards is None or self.rank is None:
          filter_row_group_indexed = [
              index for index in list(range(len(self.row_group)))
          ]
      else:
          assert self.num_shards <= len(self.row_group), (
              "num_shards should be not larger than partitions."
              "but got num_shards {} with partitions {}.".format(
                  self.num_shards, len(self.row_group)
              )
          )
          assert self.rank < self.num_shards, (
              "shard index should be included in [0,num_shard),"
              "but got rank {} with num_shard {}.".format(
                  self.rank, self.num_shards
              )
          )
          filter_row_group_indexed = [
              index
              for index in list(range(len(self.row_group)))
              if index % self.num_shards == self.rank
          ]
  
      data_record = []
      for select_chunk_path in [
          self.row_group[i] for i in filter_row_group_indexed
      ]:
          pq_table = pq.read_table(select_chunk_path)
          df = decode_feature_type_ndarray(pq_table.to_pandas(), schema)
          data_record.extend(df.to_dict("records"))
      return data_record
  
imports: from pyspark import SparkContext
  from pyspark.sql import SparkSession
  from zoo import init_nncontext
  from zoo.orca.data import SparkXShards
  from zoo.orca.data.file import open_text, write_text
  from zoo.orca.data.image.utils import chunks, dict_to_row, row_to_dict, encode_schema, decode_schema, SchemaField, FeatureType, DType, ndarray_dtype_to_dtype, decode_feature_type_ndarray, pa_fs
  from zoo.orca.data.image.voc_dataset import VOCDatasets
  from bigdl.util.common import get_node_and_core_number
  import os
  import numpy
  import random
  import pyarrow.parquet
  import io
  import math
label_desc: Use image node_id 2 for calling the ParquetIterable obj's underlying member method code with example usage: obj._load_data(schema) and returns: data_record