class_docstr: Augments a sequence with a target on the fly.
  
  Takes a sequence/generator and a function that
  creates on the fly for each batch a target.
  The generator takes a batch from that sequence,
  computes the target and returns both.
  
  :param sequence: A sequence or generator.
  :param augment_f: Takes a batch and returns a target.
class_docstr_tok: ["Augments","a","sequence","with","a","target","on","the","fly",".","Takes","a","sequence\/generator","and","a","function","that","creates","on","the","fly","for","each","batch","a","target",".","The","generator","takes","a","batch","from","that","sequence",",","computes","the","target","and","returns","both",".",":","param","sequence",":","A","sequence","or","generator",".",":","param","augment_f",":","Takes","a","batch","and","returns","a","target","."]
code: def __len__(self) -> int:
      return len(self.sequence)
  
file_path: innvestigate/src/innvestigate/utils/sequence.py
imports: from __future__ import annotations
  import math
  from typing import Callable
  import tensorflow.keras.utils
  from innvestigate.backend import to_list
  from innvestigate.backend.types import OptionalList, Tensor
label_desc: Use image node_id 2 for calling the TargetAugmentedSequence obj's underlying member method code with example usage: obj.__len__() and returns: len