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我有几个不同模型的保存点，我想在另一台机器（Kaggle）上进行评估，但似乎找不到任何关于如何恢复 hdf5 文件并从该点启动 BayesSearchCV 的文档。

这是我创建 BayesSearchCV 并将回调保存为 .hdf5 的方法

任何帮助深表感谢！

search_space = dict()
search_space["epochs"] = Integer(125, 155, 'uniform')
search_space["batch_size"] = Integer(165, 220, 'uniform')

def bayes_search(filepath, model):
    checkpoint_callback = skopt.callbacks.CheckpointSaver(filepath)
    NN_start = process_time()
    estimator= KerasClassifier (build_fn=model,  verbose=0)# , epochs=220, batch_size=256 
    bayes = BayesSearchCV(estimator, search_spaces=search_space, cv=3)
    fit_CV = bayes.fit(X_train, y_train, callback=[checkpoint_callback])
    NN_stop = process_time()
    print("Elapsed time during BayesCV in minutes:", ((NN_stop - NN_start) /60))
    print(fit_CV.best_params_)
    return fit_CV, bayes

# Define Model
def buildmodel1(optimizer = 'adam'):
    model = Sequential()
    model.add(Dense(784, activation='selu',input_dim=784, kernel_initializer="he_normal", use_bias = True))
    layers.Dropout(rate=0.4)

    model.add(Dense(150, activation='selu', kernel_initializer="he_normal", use_bias = True))
    layers.Dropout(rate=0.25)
    model.add(Dense(150, activation='selu', kernel_initializer="he_normal"))
    layers.Dropout(rate=0.25)
    model.add(Dense(150, activation='selu', kernel_initializer="he_normal"))
    layers.Dropout(rate=0.25)
    model.add(Dense(150, activation='selu', kernel_initializer="he_normal"))
    layers.Dropout(rate=0.25)
    model.add(Dense(150, activation='selu', kernel_initializer="he_normal"))
    layers.Dropout(rate=0.25)
    model.add(Dense(10, activation='softmax', kernel_initializer="he_normal"))
    # compile the keras model
    model.compile(loss='sparse_categorical_crossentropy', optimizer='adam',  metrics=['accuracy']) 
    # fit the keras model on the dataset
    #model.fit(X_train, y_train, epochs=152, batch_size=176)
    # evaluate the keras model
    #_, accuracy = model.evaluate(X_val, y_val)
    
    return(model)

# Save for import to Kaggle
filepath = 'my_best_model1.hdf5'

model1_bayesCV, cv_instance = bayes_search(filepath, buildmodel1)
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