class_docstr: Represents a distributed set of elements backed by an RDD,
  which is created by applying tensorflow dataset transformations
  on each partitions.
code: def __init__(
      self,
      xshards: "SparkXShards",
      create_dataset_fn: Callable,
      xshards_transform_fn: Optional[Callable] = None,
  ) -> None:
      self.xshards = xshards
      self.create_dataset_fn = create_dataset_fn
      self.xshards_transform_fn = xshards_transform_fn
  
imports: import tensorflow
  from bigdl.orca.tfpark.tf_dataset import TensorMeta
  from bigdl.dllib.utils import nest
  from bigdl.orca.data import SparkXShards
  from bigdl.dllib.utils import log4Error
  from bigdl.dllib.utils.log4Error import invalidInputError
  from typing import TYPE_CHECKING, Callable, Optional, Any
label_desc: Use image node_id 1 to create a new Dataset object from inherited base classes: object with example: obj = Dataset(xshards, create_dataset_fn, xshards_transform_fn)