code: def test_fprop(self):
      import tensorflow as tf
  
      model = KerasModelWrapper(self.model)
      x = tf.placeholder(tf.float32, shape=(None, 100))
      out_dict = model.fprop(x)
  
      self.assertEqual(
          set(out_dict.keys()), set(["l1", "l2", "softmax"])
      )
      # Test the dimension of the hidden represetation
      self.assertEqual(int(out_dict["l1"].shape[1]), 20)
      self.assertEqual(int(out_dict["l2"].shape[1]), 10)
  
      # Test the caching
      x2 = tf.placeholder(tf.float32, shape=(None, 100))
      out_dict2 = model.fprop(x2)
      self.assertEqual(
          set(out_dict2.keys()), set(["l1", "l2", "softmax"])
      )
      self.assertEqual(int(out_dict2["l1"].shape[1]), 20)
  
file_path: cleverhans/cleverhans_v3.1.0/tests_tf/test_utils_keras.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import unittest
  import numpy
  from tensorflow import keras
  from cleverhans.utils_keras import KerasModelWrapper
label_desc: Use image node_id 7 for calling the TestKerasModelWrapper obj's underlying member method code with example usage: obj.test_fprop() without return types