fcn16s_loss = keras.losses.SparseCategoricalCrossentropy()
fcn16s_model.compile(optimizer=fcn16s_optimizer,loss=fcn16s_loss,metrics=[keras.
metrics.MeanIoU(num_classes=NUM_CLASSES, sparse_y_pred=False),keras.metrics.
SparseCategoricalAccuracy(),],)

fcn16s_history = fcn16s_model.fit(train_ds, epochs=EPOCHS, validation_data=valid_ds)

fcn8s_optimizer = keras.optimizers.AdamW(learning_rate=LEARNING_RATE, weight_decay=WEIGHT_DECAY)

fcn8s_loss = keras.losses.SparseCategoricalCrossentropy()
fcn8s_model.compile(optimizer=fcn8s_optimizer,loss=fcn8s_loss,metrics=[keras.
metrics.MeanIoU(num_classes=NUM_CLASSES, sparse_y_pred=False),keras.metrics.
SparseCategoricalAccuracy(),],)

fcn8s_history = fcn8s_model.fit(train_ds, epochs=EPOCHS, validation_data=valid_ds)