class_docstr: A way to generate a dataset.
  
  The factory itself should be cheap to create, though it may take some time to actually generate
  the dataset.
class_docstr_tok: ["A","way","to","generate","a","dataset",".","The","factory","itself","should","be","cheap","to","create",",","though","it","may","take","some","time","to","actually","generate","the","dataset","."]
docstr: Create the dataset.
  
  This method should be deterministic - if called multiple times it should return the same
  data. If you need randomness, please use a fixed seed.
  
  :param cache_dir: A directory you can use to read/write any cache data.
docstr_tok: ["Create","the","dataset",".","This","method","should","be","deterministic","-","if","called","multiple","times","it","should","return","the","same","data",".","If","you","need","randomness",",","please","use","a","fixed","seed",".",":","param","cache_dir",":","A","directory","you","can","use","to","read\/write","any","cache","data","."]
code: def create_dataset(self, cache_dir: Path) -> Dataset:
      """
      Create the dataset.
  
      This method should be deterministic - if called multiple times it should return the same
      data. If you need randomness, please use a fixed seed.
  
      :param cache_dir: A directory you can use to read/write any cache data.
      """
  
imports: import zipfile
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from functools import wraps
  from pathlib import Path
  from typing import AbstractSet, Callable, Optional, Tuple
  from urllib.parse import urlparse
  from urllib.request import urlopen
  import numpy
  import pandas
  from check_shapes import check_shapes
  from benchmark.registry import TaggedRegistry
  from benchmark.tag import Tag, TagReq
  from gpflow.base import AnyNDArray
label_desc: Use image node_id 1 for calling the DatasetFactory obj's underlying member method code with example usage: obj.create_dataset(cache_dir) without return types