class_docstr: This class provides functionality to store and load activation vectors
  generated for pre-defined neural network layers.
  It also provides functionality to check if activation vectors already
  exist in the manifold and other auxiliary functions.
  
  This class also defines a torch `Dataset`, representing Activation Vectors,
  which enables lazy access to activation vectors and layer stored in the manifold.
class_docstr_tok: ["This","class","provides","functionality","to","store","and","load","activation","vectors","generated","for","pre-defined","neural","network","layers",".","It","also","provides","functionality","to","check","if","activation","vectors","already","exist","in","the","manifold","and","other","auxiliary","functions",".","This","class","also","defines","a","torch","`","Dataset","`",",","representing","Activation","Vectors",",","which","enables","lazy","access","to","activation","vectors","and","layer","stored","in","the","manifold","."]
code: def __init__(self) -> None:
      pass
  
imports: import glob
  import os
  import re
  import warnings
  from typing import Any, List, Optional, Tuple, Union
  import captum._utils.common
  import torch
  from captum.attr import LayerActivation
  from torch import Tensor
  from torch.nn import Module
  from torch.utils.data import DataLoader, Dataset
label_desc: Use image node_id 1 to create a new AV object  with example: obj = AV()