code: def setUpClass(cls):
      master_seed(seed=1234, set_tensorflow=True)
      super().setUpClass()
  
      import tensorflow as tf
      import tensorflow.keras as keras
  
      tf.compat.v1.disable_eager_execution()
  
      class TestModel(tf.keras.Model):
          def __init__(self):
              super().__init__()
              self.dense1 = keras.layers.Dense(
                  10, activation=tf.nn.relu
              )
              self.dense2 = keras.layers.Dense(
                  100, activation=tf.nn.relu
              )
              self.dense3 = keras.layers.Dense(
                  10, activation=tf.nn.relu
              )
              self.dense4 = keras.layers.Dense(1)
  
          def call(self, inputs):
              x = self.dense1(inputs)
              return self.dense4(self.dense3(self.dense2(x)))
  
      cls.keras_model = TestModel()
      cls.keras_model.compile(
          loss=keras.losses.CosineSimilarity(
              axis=-1, reduction="auto", name="cosine_similarity"
          ),
          optimizer=keras.optimizers.Adam(learning_rate=0.01),
          metrics=["accuracy"],
      )
      cls.keras_model.fit(cls.x_train_diabetes, cls.y_train_diabetes)
  
      cls.art_model = KerasRegressor(model=cls.keras_model)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  from art.estimators.regression.keras import KerasRegressor
  from tests.utils import TestBase, master_seed, get_tabular_regressor_kr
label_desc: Use image node_id 1 for calling the TestKerasRegressorClass obj's underlying member method code with example usage: obj.setUpClass(cls) and returns: self