docstr: Initialize the test class.
code: def __init__(self, methodname):
      """Initialize the test class."""
      super().__init__(methodname)
  
      self.ntrain, self.ntest = 50, 100
      self.nclass = 5
      self.ndim = 10
  
      # Generate random training and test data
      self.train_data = np.random.rand(self.ntrain, self.ndim)
      self.test_data = np.random.rand(self.ntest, self.ndim)
      self.train_labels = np.random.randint(
          self.nclass, size=self.ntrain
      )
      self.test_labels = np.random.randint(self.nclass, size=self.ntest)
  
      self.model = tf.keras.Sequential(
          [tf.keras.layers.Dense(self.nclass)]
      )
  
      loss = tf.keras.losses.SparseCategoricalCrossentropy(
          from_logits=True
      )
      self.model.compile(
          optimizer="Adam", loss=loss, metrics=["accuracy"]
      )
  
file_path: privacy/tensorflow_privacy/privacy/privacy_tests/membership_inference_attack/keras_evaluation_test.py
imports: from absl.testing import absltest
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import keras_evaluation
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackResults
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackType
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import get_flattened_attack_metrics
label_desc: Use image node_id 1 to create a new UtilsTest object from inherited base classes: absltest with example: obj = UtilsTest(methodname)