def METHOD_NAME(self):
    """Model from https://keras.io/examples/vision/mnist_convnet/."""
    model = tf.keras.Sequential(
        [
            tf.keras.Input(shape=self.input_shape),
            tf.keras.layers.Conv2D(
                32, kernel_size=(3, 3), activation="relu"
            ),
            tf.keras.layers.MaxPooling2D(pool_size=(2, 2)),
            tf.keras.layers.Conv2D(
                64, kernel_size=(3, 3), activation="relu"
            ),
            tf.keras.layers.MaxPooling2D(pool_size=(2, 2)),
            tf.keras.layers.Flatten(),
            tf.keras.layers.Dropout(0.5),
            tf.keras.layers.Dense(self.num_classes, activation="softmax"),
        ]
    )
    return model