code: def nondifferentiable_model():
      inpt = Input(shape=(1,))
      op = Lambda(lambda x: K.constant(0) if x == 0 else K.constant(1))(
          inpt
      )  # piecewise function
      model = Model(inpt, op)
      model.summary()
      return model
  
imports: import pytest
  import keras.backend
  from keras.models import Sequential, Model
  from keras.layers import Dense, Activation, Conv2D, GlobalAveragePooling2D, Input, Lambda
  from keras.backend import epsilon
  import numpy
  from eli5.keras.explain_prediction import explain_prediction, _validate_doc, _get_activation_layer
  from eli5.keras.gradcam import _get_target_prediction, _calc_gradient, gradcam
label_desc: Use image node_id 9 for calling a global function with example usage: nondifferentiable_model() and returns: model