def build_loss(self, a_image, ap_image, b_image):
        loss = K.variable(0.0)
        # get the symbolic outputs of each "key" layer (we gave them unique names).
        loss += self.args.tv_weight * total_variation_loss(self.net_input, *b_image.shape[2:])
        return loss
Stop the channel's event loop and join its thread.
dataset/ETHPy150Open awentzonline/image-analogies/image_analogy/models/base.py/BaseModel.build_loss--crossover with--dataset/ETHPy150Open jupyter/jupyter_client/jupyter_client/threaded.py/IOLoopThread.stop