Tukukkk

I was trying to write masked MSE loss:

def mae_loss_masked(mask):

    def loss_fn(y_true, y_pred):

        abs_vec = tf.multiply(tf.abs(y_pred-y_true), mask)

        loss = tf.reduce_mean(abs_vec)

        return loss

    return loss_fn

My model:

def MobileNet_v1():

    # MobileNet with dense layer on top



    # Keras 2.1.6

    mobilenet = MobileNet(input_shape=(config.IMAGE_H, config.IMAGE_W, config.N_CHANNELS),

                          alpha=1.0,

                          depth_multiplier=1,

                          include_top=False,

                          weights='imagenet'

                          )



    x = Flatten()(mobilenet.output)

    x = Dropout(0.5)(x)

    x = Dense(config.N_LANDMARKS * 2, activation='linear')(x)



    # -------------------------------------------------------



    model = Model(inputs=mobilenet.input, outputs=x)

    optimizer = Adadelta()

    model.compile(optimizer=optimizer, loss=mae_loss_masked)



    model.summary()

    import sys

    sys.exit()



    return model

But it give an error:
TypeError: mae_loss_masked() takes 1 positional argument but 2 were given

Also a question how batch generator output should look like in this case.