我很难将任何回调应用到Keras Tuner hyperparameter optimsier对象。下面是我运行的代码：

from keras.callbacks import TensorBoard, EarlyStopping
%load_ext tensorboard

BATCH_SIZE = 32

time_stamp = time.time()
tensorboard = TensorBoard(log_dir = " graphs/{}".format(time_stamp))
checkpoint = ModelCheckpoint(filepath = r"D:\Uni work\...\CNN.hdf5" , monitor = 'val_accuracy', verbose = 1, save_best_only = True )
early_stopping = EarlyStopping( monitor="val_loss" , patience= 3, verbose=2)

tuner = BayesianOptimization(build_model, objective = "val_accuracy", max_trials = 30, num_initial_points=2,  project_name ="audio_classifier")

tuner.search(x = train_X, y=y_cat_encoded, epochs=35, callbacks =  early_stopping, batch_size = BATCH_SIZE, validation_data = (validation_X, y_validation_cat_encoded))

虽然我想应用tensorboard和checkpoint回调，但它只是通过传递提前停止回调而失败。我得到以下错误：

C:\Anaconda\envs\test\lib\site-packages\kerastuner\engine\tuner.py in _deepcopy_callbacks(self, callbacks)
    277             callbacks = copy.deepcopy(callbacks)
    278         except:
--> 279             raise ValueError(
    280                 'All callbacks used during a search '
    281                 'should be deep-copyable (since they are '

ValueError: All callbacks used during a search should be deep-copyable (since they are reused across trials). It is not possible to do `copy.deepcopy(<tensorflow.python.keras.callbacks.EarlyStopping object at 0x000001802D138100>)

我不太熟悉deep-copyable这个术语，也不知道它在错误代码方面意味着什么。有人知道如何解决这个问题吗？