code: def setUp(self):
      super().setUp()
      self.input_shape = (12, 12, 3)
      self.num_classes = 10
      self.batch_size = 8
      self.batched_input_shape = tuple(
          [self.batch_size] + list(self.input_shape)
      )
      self.model = tf.keras.Sequential(
          [
              tf.keras.Input(shape=self.input_shape, dtype=tf.float32),
              tf.keras.layers.Flatten(),
              tf.keras.layers.Dense(self.num_classes),
          ]
      )
      self.loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(
          from_logits=True, reduction=tf.keras.losses.Reduction.NONE
      )
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/attacks_test.py
imports: from absl.testing import parameterized
  import gin
  from multi_representation_adversary import attacks
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 1 for calling the AttacksTest obj's underlying member method code with example usage: obj.setUp() without return types