def METHOD_NAME(self):
    augmenter0 = preprocessing.RandomFlip("horizontal")
    augmenter1 = preprocessing.RandomFlip("vertical")
    projector0 = layers.Dense(64, name="projector0")
    projector1 = keras.Sequential(
        [projector0, layers.ReLU(), layers.Dense(64, name="projector1")]
    )
    trainer_without_probing = ContrastiveTrainer(
        encoder=self.build_encoder(),
        augmenter=(augmenter0, augmenter1),
        projector=(projector0, projector1),
        probe=None,
    )
    images = tf.random.uniform((1, 50, 50, 3))
    trainer_without_probing.compile(
        encoder_optimizer=optimizers.Adam(),
        encoder_loss=SimCLRLoss(temperature=0.5),
    )
    trainer_without_probing.fit(images)