class_docstr: DIExplainer is the base class for Directly Interpretable unsupervised explainers (DIE).
  Such explainers generally rely on unsupervised techniques to explain datasets and model predictions.
  Examples include DIP-VAE[#1]_, Protodash[#2]_, etc.
  
  References:
      .. [#1] Variational Inference of Disentangled Latent Concepts from Unlabeled Observations (DIP-VAE), ICLR 2018.
       Kumar, Sattigeri, Balakrishnan. https://arxiv.org/abs/1711.00848
      .. [#2] ProtoDash: Fast Interpretable Prototype Selection, 2017.
      Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo Cecchi.
      https://arxiv.org/abs/1707.01212
docstr: Initialize a DIExplainer object.
  ToDo: check common steps that need to be distilled here.
docstr_tok: ["Initialize","a","DIExplainer","object",".","ToDo",":","check","common","steps","that","need","to","be","distilled","here","."]
code: def __init__(self, *argv, **kwargs):
      """
      Initialize a DIExplainer object.
      ToDo: check common steps that need to be distilled here.
      """
  
imports: import abc
  import sys
label_desc: Use image node_id 1 to create a new DIExplainer object from inherited base classes: ABC with example: obj = DIExplainer()