x_train_scaled_wide , x_train_scaled_deep = x_train_scaled[:,:5], x_train_scaled[:,2:]

x_test_scaled_wide , x_test_scaled_deep = x_test_scaled[:,:5], x_test_scaled[:,2:]

x_valid_scaled_wide , x_valid_scaled_deep = x_valid_scaled[:,:5], x_valid_scaled[:,2:]

class WideDeepModel(keras.models.Model):

    def __init__(self):

        super(WideDeepModel, self).__init__()

        self.hidden1 = tf.keras.layers.Dense(30,activation='relu')

        self.hidden2 = tf.keras.layers.Dense(30,activation='relu')

        self.output_layer = tf.keras.layers.Dense(1)

    def __call__(self,inputs):

#       转换数据

        input_wide, input_deep = inputs

        input_wide = tf.keras.layers.Input(shape=[5])

        input_deep = tf.keras.layers.Input(shape=[6])

        h1 = self.hidden1(input_deep)

        h2 = self.hidden2(h1)

        concat = tf.keras.layers.concatenate([input_wide,h2])

        output = self.output_layer(concat)

        return output

model = WideDeepModel()

model.compile(loss="mean_squared_error", optimizer=keras.optimizers.SGD(1e-3))

history = model.fit([x_train_scaled_wide, x_train_scaled_deep], 

                    y_train, epochs=3,

                    validation_data=(

                        [x_valid_scaled_wide, x_valid_scaled_deep], 

                         y_valid),

            )

问题：

Train on 11610 samples, validate on 3870 samples
Epoch 1/3
  32/11610 [..............................] - ETA: 2s

TypeError: __call__() got an unexpected keyword argument 'training'