docstr: Export rolling result in form of a dict of numpy ndarray {'x': ..., 'y': ..., 'id': ...},
  where value for 'x' and 'y' are 3-dim numpy ndarray and value for 'id' is 2-dim ndarray
  with shape (batch_size, 1)
  
  :param partition_num: how many partition you would like to split your data.
  
  :return: a 3-element dict xshard. each value is a 3d numpy ndarray. The ndarray
           is casted to float32. Default to None which will partition according
           to id.
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code: def to_xshards(self, partition_num=None):
      """
      Export rolling result in form of a dict of numpy ndarray {'x': ..., 'y': ..., 'id': ...},
      where value for 'x' and 'y' are 3-dim numpy ndarray and value for 'id' is 2-dim ndarray
      with shape (batch_size, 1)
  
      :param partition_num: how many partition you would like to split your data.
  
      :return: a 3-element dict xshard. each value is a 3d numpy ndarray. The ndarray
               is casted to float32. Default to None which will partition according
               to id.
      """
      from bigdl.nano.utils.common import invalidInputError
  
      if self.numpy_shards is None:
          invalidInputError(
              False,
              "Please call 'roll' method "
              "before transform a XshardsTSDataset to numpy ndarray!",
          )
      if partition_num is None:
          return self.numpy_shards.transform_shard(transform_to_dict)
      else:
          return self.numpy_shards.transform_shard(
              transform_to_dict
          ).repartition(partition_num)
  
imports: from bigdl.orca.data.shard import SparkXShards
  from bigdl.orca.learn.utils import dataframe_to_xshards_of_pandas_df
  from bigdl.chronos.data.utils.utils import _to_list, _check_type
  from bigdl.chronos.data.utils.roll import roll_timeseries_dataframe
  from bigdl.chronos.data.utils.impute import impute_timeseries_dataframe
  from bigdl.chronos.data.utils.split import split_timeseries_dataframe
  from bigdl.chronos.data.experimental.utils import add_row, transform_to_dict
  from bigdl.chronos.data.utils.scale import unscale_timeseries_numpy
  from bigdl.chronos.data.utils.feature import generate_dt_features
  import pandas
label_desc: Use image node_id 10 for calling the XShardsTSDataset obj's underlying member method code with example usage: obj.to_xshards(partition_num) and returns: self, self