class_docstr: Abstract class for defining an input modifier. An input modifier can be used with the
  [Optimizer.minimize](vis.optimizer.md#optimizerminimize) to make `pre` and `post` changes to the optimized input
  during the optimization process.
  
  ```python
  modifier.pre(seed_input)
  # gradient descent update to img
  modifier.post(seed_input)
  ```
docstr: Implement post gradient descent update modification to the input. If post-processing is not desired,
  simply ignore the implementation. It returns the unmodified `inp` by default.
  
  Args:
      inp: An N-dim numpy array of shape: `(samples, channels, image_dims...)` if `image_data_format=
          channels_first` or `(samples, image_dims..., channels)` if `image_data_format=channels_last`.
  
  Returns:
      The modified post input.
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code: def post(self, inp):
      """Implement post gradient descent update modification to the input. If post-processing is not desired,
      simply ignore the implementation. It returns the unmodified `inp` by default.
  
      Args:
          inp: An N-dim numpy array of shape: `(samples, channels, image_dims...)` if `image_data_format=
              channels_first` or `(samples, image_dims..., channels)` if `image_data_format=channels_last`.
  
      Returns:
          The modified post input.
      """
      return inp
  
file_path: keras-vis/vis/input_modifiers.py
imports: from __future__ import absolute_import
  import numpy
  from scipy.ndimage.interpolation import shift
  from .utils import utils
  from keras import backend
label_desc: Use image node_id 2 for calling the InputModifier obj's underlying member method code with example usage: obj.post(inp) and returns: inp