求大神帮忙看看程序哪里有问题

mmf827950280

# 载入FD001数据集
file_load = 'd:/python_keras/predict aircraft engineer RUL/Dataset/PM_train_guiyihua.csv'
train_df = pd.read_csv(file_load, encoding='gbk')
# print(train_df)
new_features = ['cycle_norm', 's4', 's11', 's12', 's9', 's7', 's14', 's15',
                's21', 's2', 's3', 's20', 'setting1', 's13', 's8', 's17']
x_t = train_df[new_features]
y_t = train_df['RUL']

# 模型参数设置
# 对模型进行优化（每层神经元数量， 每层丢弃率, 迭代步数， 批次样本数）
d = [0.05, 0.1, 0.2, 0.3, 0.4, 0.5]
neuron = [1024, 512, 256, 128, 64, 32]
epochs = [10, 20, 50, 100, 1000]
batch_size = [10, 25, 50, 100, 200]
seq_length = [10, 20, 30, 50]

def model_t_c(d, n1, n2):
    model = Sequential()
    model.add(GRU(n1, input_shape=(1, 16)))
    model.add(Dropout(d))
    model.add(Dense(n2, activation='sigmoid'))
    model.add(Dense(1, activation='linear'))

    model.compile(optimizer='rmsprop', loss='mse', metrics='mae')
    model.summary()
    return model

model_t = model_t_c(0.2, 256, 256)

# 贝叶斯优化
hyperparameters = {"d": Real(0, 1, prior='log-uniform'), "n1":Real(0, 1e4, prior='uniform'), "n2":Real(0, 1e4, prior='uniform')}
Kmodel = KerasClassifier(build_fn=model_t, verbose=1)
bayesian = BayesSearchCV(estimator = Kmodel, search_spaces = hyperparameters, n_iter = 200, cv = 5, random_state=42, n_jobs = -1, scoring='neg_mean_squared_error')
bayesian.fit(x_t, y_t)
print(f'Best parameters: {bayesian.best_params_}')
print(f'Best score: {bayesian.best_score_}')

执行上述代码之后会出现下面的错误，目前没有找到解决方案
TypeError: can't pickle _thread.RLock objects

suchocolate

pickle只能保存python基本类型的对象，如列表，字典。thread.RLock应该是模块中定义的对象，所以不能保存。