code: def build_loss(self):
      # Infinity norm
      if np.isinf(self.p):
          value = K.max(self.img)
      else:
          value = K.pow(
              K.sum(K.pow(K.abs(self.img), self.p)), 1.0 / self.p
          )
  
      return normalize(self.img, value)
  
file_path: keras-vis/vis/regularizers.py
imports: from __future__ import absolute_import
  from __future__ import division
  import numpy
  from keras import backend
  from .losses import Loss
  from .utils import utils
label_desc: Use image node_id 2 for calling the LPNorm obj's underlying member method code with example usage: obj.build_loss() and returns: normalize