def METHOD_NAME(self):
    trainer_with_probing = ContrastiveTrainer(
        encoder=self.build_encoder(),
        augmenter=self.build_augmenter(),
        projector=self.build_projector(),
        probe=self.build_probe(),
    )
    trainer_without_probing = ContrastiveTrainer(
        encoder=self.build_encoder(),
        augmenter=self.build_augmenter(),
        projector=self.build_projector(),
        probe=None,
    )
    images = tf.random.uniform((1, 50, 50, 3))
    trainer_with_probing.compile(
        encoder_optimizer=optimizers.Adam(),
        encoder_loss=SimCLRLoss(temperature=0.5),
        probe_optimizer=optimizers.Adam(),
        probe_loss=keras.losses.CategoricalCrossentropy(from_logits=True),
    )
    trainer_without_probing.compile(
        encoder_optimizer=optimizers.Adam(),
        encoder_loss=SimCLRLoss(temperature=0.5),
    )
    with self.assertRaises(ValueError):
        trainer_with_probing.fit(images)