train_val_FCN_DA.py 文件源码

def on_batch_end(self, batch, logs={}):
        if np.isnan(logs.get('loss')): #Model contain NaN
            print('NaN detected, reloading model')
            self.model.compile(optimizer=Adadelta(),
              loss={'output': SP_pixelwise_loss, 'output_2': layout_loss_hard},
              loss_weights={'output': 1.,'output_2':0.1})
            self.model.load_weights(output_name)