class_docstr: Keras compatible data generator that wraps a Keras Sequence and provides corrupted
  data for training Deep Graph Infomax.
  
  Args:
      base_sequence: the uncorrupted Sequence object.
      corrupt_index_groups: the groups among which nodes will be shuffled (see :class:`.CorruptedGenerator` for more details)
      num_batch_dims: the number of axes that are "batch" dimensions
class_docstr_tok: ["Keras","compatible","data","generator","that","wraps","a","Keras","Sequence","and","provides","corrupted","data","for","training","Deep","Graph","Infomax",".","Args",":","base_sequence",":","the","uncorrupted","Sequence","object",".","corrupt_index_groups",":","the","groups","among","which","nodes","will","be","shuffled","(","see",":","class",":","`",".CorruptedGenerator","`","for","more","details",")","num_batch_dims",":","the","number","of","axes","that","are","``","batch","''","dimensions"]
code: def __len__(self):
      return len(self.base_sequence)
  
file_path: stellargraph/stellargraph/mapper/corrupted.py
imports: import numpy
  from tensorflow.keras.utils import Sequence
  from .None import Generator
  from ..core.validation import comma_sep
label_desc: Use image node_id 2 for calling the CorruptedSequence obj's underlying member method code with example usage: obj.__len__() and returns: len