Closed yilawu closed 2 years ago
I got some guidance from the author on the details, and I go on with the experiment. Thanks very much !!!
I got some guidance from the author on the details, and I go on with the experiment. Thanks very much !!!
Hello, I ran into the same issue, where the results between ASSL and L1-pruning are quite similar. I wonder how did you solve this and if the ASSL result distinguished itself, thanks in advance!
I got some guidance from the author on the details, and I go on with the experiment. Thanks very much !!!
Hello, I ran into the same issue, where the results between ASSL and L1-pruning are quite similar. I wonder how did you solve this and if the ASSL result distinguished itself, thanks in advance!
@wurongyuan @MingSun-Tse Hello,I also have same question. And I find that the result of ASSL and L1 pruning is similar to EDSR_16_49 model training from scratch, is there something wrong in initialization or params copy?
hello , I have some questiones about implementation details.
Data are obtained using the HR-LR data pairs obtained by the down-sampling code provided in BasicSR. The training data was DF2K (900 DIV2K + 2650 Flickr2K), and the test data was Set5.
I run this command to prune the EDSR_16_256 model to EDSR_16_48. Only the pruning ratio and storage path name are modified compared to the command provided by the official.
Prune from 256 to 48, pr=0.8125, x2, ASSL
The result (37.940dB) I obtained with the code provided by the official is still a certain gap from the result in the paper (38.12dB). I should have overlooked some details. # I also compared L1-norm method provided in the code. Prune from 256 to 48, pr=0.8125, x2, L1
Results
The difference between the results of L1-norm method and those of ASSL seems negligible at this pruning ratio (256->48) #
Is there something I missed? Looking forward to your reply! >-<