code: def build_model(self):
      model = tf.keras.Sequential(
          [
              tf.keras.layers.Dense(
                  8,
                  input_shape=(
                      8,
                      8,
                  ),
              )
          ]
      )
      model = self.context.wrap_model(model)
      # TODO MLG-443 Migrate from legacy Keras optimizers
      if version.parse(tf.__version__) >= version.parse("2.11.0"):
          optimizer = self.context.wrap_optimizer(
              tf.keras.optimizers.legacy.SGD()
          )
      else:
          optimizer = self.context.wrap_optimizer(
              tf.keras.optimizers.SGD()
          )
      model.compile(
          loss=tf.keras.losses.MeanSquaredError(),
          optimizer=optimizer,
          metrics=[
              RandomMetric(name="rand_rand"),
              NumPyRandomMetric(name="np_rand"),
              TensorFlowRandomMetric(name="tf_rand"),
          ],
      )
      return model
  
imports: import random
  import numpy
  import tensorflow
  from packaging import version
  from determined.keras import TFKerasTrial, TFKerasTrialContext
label_desc: Use image node_id 2 for calling the NoopKerasTrial obj's underlying member method code with example usage: obj.build_model() and returns: model