无法克隆对象 <tensorflow.python.keras.wrappers.scikit_learn.KerasClassifier 对象

Question

这是关于 TF 2.0。

请在我的代码下方找到执行 GridSearch 和交叉验证的代码，这些代码sklearn.model_selection.GridSearchCV用于 mnist 数据集，效果非常好。

# Build Function to create model, required by KerasClassifier

    def create_model(optimizer_val='RMSprop',hidden_layer_size=16,activation_fn='relu',dropout_rate=0.1,regularization_fn=tf.keras.regularizers.l1(0.001),kernel_initializer_fn=tf.keras.initializers.glorot_uniform,bias_initializer_fn=tf.keras.initializers.zeros):
        model = tf.keras.models.Sequential([
        tf.keras.layers.Flatten(input_shape=(28, 28)),    
        tf.keras.layers.Dense(units=hidden_layer_size, activation=activation_fn,kernel_regularizer=regularization_fn,kernel_initializer=kernel_initializer_fn,bias_initializer=bias_initializer_fn), 
        tf.keras.layers.Dropout(dropout_rate),
        tf.keras.layers.Dense(units=hidden_layer_size,activation='softmax',kernel_regularizer=regularization_fn,kernel_initializer=kernel_initializer_fn,bias_initializer=bias_initializer_fn) 
          ])
        optimizer_val_final=optimizer_val
        model.compile(optimizer=optimizer_val, loss='sparse_categorical_crossentropy', metrics=['accuracy'])
        return model

    #Create the model with the wrapper
    model = tf.keras.wrappers.scikit_learn.KerasClassifier(build_fn=create_model, epochs=100, batch_size=10, verbose=2)

    #Initialize the parameter grid
    nn_param_grid = {
        'epochs': [10],     
        'batch_size':[128],
        'optimizer_val': ['Adam','SGD'],
        'hidden_layer_size': [128],
        'activation_fn': ['relu'],     
        'dropout_rate': [0.2],    
        'regularization_fn':['l1','l2','L1L2'],    
        'kernel_initializer_fn':['glorot_normal', 'glorot_uniform'],    
        'bias_initializer_fn':[tf.keras.initializers.zeros]    
    }
    #Perform GridSearchCV
    grid = GridSearchCV(estimator=model, param_grid=nn_param_grid, verbose=2, cv=3,scoring=precision_custom,return_train_score=False,n_jobs=-1) 
    grid_result = grid.fit(x_train, y_train)

我的想法是通过具有不同学习率的不同优化器，比如 Adam 的学习率 0.1、0.01 和 0.001。我还想尝试使用不同学习率和动量值的 SGD。

在这种情况下，当我通过时'optimizer_val': [tf.keras.optimizers.Adam(0.1)],，我收到如下错误：

Cannot clone object <tensorflow.python.keras.wrappers.scikit_learn.KerasClassifier object at 0x7fe08b210e10>, as the constructor either does not set or modifies parameter optimizer_val

请告知我如何纠正此错误。

Answer 1

这是sklearn错误。您应该减少 sklearn 的版本：

conda install scikit-learn==0.21.2

没关系！