class_docstr: Abstract Class to describe the interface of a trainable model to be used
  within the algorithms of captum.
  
  Please note that this is an experimental feature.
docstr: Returns the underlying representation of the interpretable model. For a
  linear model this is simply a tensor (the concatenation of weights
  and bias). For something slightly more complicated, such as a decision
  tree, this could be the nodes of a decision tree.
  
  Returns:
      A Tensor describing the representation of the model.
code: def representation(self) -> Tensor:
      r"""
      Returns the underlying representation of the interpretable model. For a
      linear model this is simply a tensor (the concatenation of weights
      and bias). For something slightly more complicated, such as a decision
      tree, this could be the nodes of a decision tree.
  
      Returns:
          A Tensor describing the representation of the model.
      """
      pass
  
file_path: captum/captum/_utils/models/model.py
imports: from abc import ABC, abstractmethod
  from typing import Dict, Optional, Union
  from captum._utils.typing import TensorOrTupleOfTensorsGeneric
  from torch import Tensor
  from torch.utils.data import DataLoader
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.representation() without return types