code: def evaluate_model(model):
      model.compile(
          metrics=[
              tf.keras.metrics.SparseCategoricalAccuracy(
                  name="accuracy"
              )
          ],
      )
      _, (x_test, y_test) = get_dataset()
      results = model.evaluate(
          x_test, y_test, batch_size=128, return_dict=True
      )
      return results["accuracy"]
  
imports: import os
  import shutil
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.common.keras.compression.algorithms import epr
label_desc: Use image node_id 4 for calling a global function with example usage: evaluate_model(model) and returns: results