0

我一直在尝试使用 Talos 1.0.0 实现一个简单的 MLP 以进行超参数调整,但遇到了语法错误。下面是代码片段:

    def get_model(x_train, y_train, x_val, y_val, params):
        dim = x_train.shape[1]

        model = Sequential()
        model.add(BatchNormalization(input_dim=dim))
        model.add(Dense(params['first_neuron'], activation=params['activation'], kernel_initializer='he_uniform')

        hidden_layers(model, params, 1)

        model.add(Dense(units = 1, activation = 'sigmoid'))

        model.compile(optimizer=params['optimizer'], loss=params['losses'], metrics=['acc'])

        history = model.fit(x_train, y_train, batch_size=params['batch_size'], epochs=params['epochs'], 
                    verbose=0, class_weight=class_weights, validation_data=[x_val, y_val], 
                    callbacks=[early_stopper(epochs=params['epochs'], mode='moderate', monitor='val_loss')])

        return history, model

注意:我都尝试过,从 talos.model(从 talos.model 导入 hidden_​​layers)和从 talos.utils(从 talos.utils 导入 hidden_​​layers)导入 hidden_​​layers()。任何人都可以帮助识别和解决问题吗?

4

0 回答 0