Open ibopeng opened 5 years ago
In GCN preporcessing, if a tensor x has the same feature values (e.g., a pixel with RGB = [255, 255, 255]), after mean removal, the L1-norm scale would be equal to 0, which results in 0 / 0. How would you avoid this? Thanks.
我是这样做的,当0/0时会输出nan,将所有结果的列表输出,再将列表中的nan剔除,重新拍去找到最大和最小
In GCN preporcessing, if a tensor x has the same feature values (e.g., a pixel with RGB = [255, 255, 255]), after mean removal, the L1-norm scale would be equal to 0, which results in 0 / 0. How would you avoid this? Thanks.