docstr: return a orca.data.tf.data.Dataset
  :param path:
  :return:
docstr_tok: ["return","a","orca.data.tf.data.Dataset",":","param","path",":",":","return",":"]
code: def read_as_tf(path: str) -> "TensorSliceDataset":
      """
      return a orca.data.tf.data.Dataset
      :param path:
      :return:
      """
      from bigdl.orca.data.tf.data import Dataset
  
      xshards = ParquetDataset._read_as_xshards(path)
      return Dataset.from_tensor_slices(xshards)
  
imports: from pyspark import SparkContext
  from pyspark.sql import SparkSession
  from bigdl.dllib.nncontext import init_nncontext
  from bigdl.orca.data import SparkXShards
  from bigdl.orca.data.file import open_text, write_text
  from bigdl.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 bigdl.orca.data.image.voc_dataset import VOCDatasets
  from bigdl.dllib.utils.common import get_node_and_core_number
  import os
  import numpy
  import random
  import io
  import math
  from bigdl.dllib.utils.log4Error import invalidInputError
  from numpy import ndarray, uint32
  from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Tuple, Union, Any
label_desc: Use image node_id 4 for calling the ParquetDataset obj's underlying member method code with example usage: obj.read_as_tf(path) and returns: Dataset