class_docstr: Base class for the obfuscation datasets.
  
  This class provides the functionality required to run experiments with TPU
  support, via the input_fn function. Subclasses should implement the
  _read_dataset method, in order to read the input data from its respective
  source.
  
  Attributes:
    data_dir: Directory from which to read the data.
    split: Name of the split used (one of 'train' or 'test').
    batch_size: Batch size for the data.
    is_train: Whether the dataset is used for training or not.
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code: def __init__(self, data_dir: str, batch_size: int, split: str):
      self.data_dir = data_dir
      self.batch_size = batch_size
      self.split = split
      self.is_train = split.startswith("train")
  
imports: import abc
  from typing import Optional, Sequence, Tuple
  from meo.mlp_baseline import data_utils
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 1 to create a new ObfuscatedDatasetBase object from inherited base classes: object with example: obj = ObfuscatedDatasetBase(data_dir, batch_size, split)