class_docstr: Concepts are human-friendly abstract representations that can be
  numerically encoded into torch tensors. They can be illustrated as
  images, text or any other form of representation. In case of images,
  for example, "stripes" concept can be represented through a number
  of example images resembling "stripes" in various different
  contexts. In case of Natural Language Processing, the concept of
  "happy", for instance, can be illustrated through a number of
  adjectives and words that convey happiness.
code: def identifier(self) -> str:
      return "%s-%s" % (self.name, self.id)
  
file_path: captum/captum/concept/_core/concept.py
imports: from typing import Callable, Union
  import torch
  from torch.nn import Module
label_desc: Use image node_id 2 for calling the Concept obj's underlying member method code with example usage: obj.identifier() and returns: unknown