code: def preprocess_input(x, **kwargs):
      kwargs = {
          k: v
          for k, v in kwargs.items()
          if k in ["backend", "layers", "models", "utils"]
      }
      return _preprocess_input(x, mode="torch", **kwargs)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import math
  import string
  import collections
  from six.moves import xrange
  from keras_applications.imagenet_utils import _obtain_input_shape
  from keras_applications.imagenet_utils import preprocess_input
  from .None import get_submodules_from_kwargs
  from .weights import IMAGENET_WEIGHTS_PATH, IMAGENET_WEIGHTS_HASHES, NS_WEIGHTS_HASHES, NS_WEIGHTS_PATH
label_desc: Use image node_id 1 for calling a global function with example usage: preprocess_input(x) and returns: _preprocess_input