Closed sanyalsunny111 closed 1 year ago
Thanks for your attention to our work!
Sorry for the late reply.
We have uploaded the teacher logits files, which were generated by CLIP-ViT-Large/14-22k on ImageNet-22k (Ref. the tutorial).
You can download them by azcopy.
azcopy cp "https://tracking2019.blob.core.windows.net/tinyvit-teacher-logits/clip_224_22k_top100_logits_bs128/?sv=2020-04-08&st=2022-10-26T02%3A29%3A41Z&se=2022-11-09T02%3A29%3A00Z&sr=c&sp=rl&sig=4bkaC8KkG9n2CUv%2BwbE6aVOi%2Fp3yZQnt3vQeIXW6Bc8%3D" ./ --recursive
There are 1440 files (90 epochs * 8 ranks * (key + value files)
) about 499 GB (18GB for keys, 481GB for values).
You can download the logits in the specific epoch. For example, download the logits in the epoch 0:
azcopy cp "https://tracking2019.blob.core.windows.net/tinyvit-teacher-logits/clip_224_22k_top100_logits_bs128/logits_top100_epoch0/?sv=2020-04-08&st=2022-10-26T02%3A29%3A41Z&se=2022-11-09T02%3A29%3A00Z&sr=c&sp=rl&sig=4bkaC8KkG9n2CUv%2BwbE6aVOi%2Fp3yZQnt3vQeIXW6Bc8%3D" ./ --recursive
The expiration time is Nov. 09, 2022. We can extend the date if necessary : ).
Close it. Feel free to re-open it if necessary for extending the date : )
Could you please extend the date? Thanks a lot !
Could you please extend the date? Thanks a lot !
Hi @HaoWuSR , the date has been extended.
Hello Sir could you also share the logits of teacher based on datasets such as imagenet-1K and any other dataset?
Hi @sanyalsunny111 , sorry that I did not prepare the teacher logits on ImageNet-1k for this codebase.
You can follow the tutorial to save the sparse logits.
Thank you for responding @wkcn Could you please provide a running script that could be used to save sparse logits of CLIP-ViT-Large/14-22k with imagenet-1k? I am asking cause I see save_logits.py can use both imagenet-22k and imagenet-1k. Any feedback on this?
Hi @sanyalsunny111, the following command is used to save sparse logits of CLIP-ViT-Large/14-22k on ImageNet-1k.
python -m torch.distributed.launch --nproc_per_node 8 save_logits.py --cfg configs/teacher/clip_vit_large_patch14_22k.yaml --data-path ./ImageNet --batch-size 128 --eval --resume checkpoints/clip_vit_large_patch14_22k.pth --opts DISTILL.TEACHER_LOGITS_PATH ./teacher_logits_1k AUG.MIXUP 0.8 AUG.CUTMIX 1.0 DATA.DATASET imagenet TRAIN.EPOCHS 300 DISTILL.LOGITS_TOPK 10
It needs the extra config options AUG.MIXUP 0.8 AUG.CUTMIX 1.0 DATA.DATASET imagenet TRAIN.EPOCHS 300 DISTILL.LOGITS_TOPK 10
to save the 1k logits.
However, I recommend Swin-base/large 22kto1k or BEiT-base/large 22kto1k as the 1k teacher model, since CLIP-ViT-Large/14-22k is not finetuned on ImageNet-1k.
Hi @wkcn Thank you very much for earlier responses. I have saved the teacher logits on teacher CLIP-ViT-Large/14-22k using ImageNet-1k. Could you please provide a pre-training script (with distillation) with saved teacher logits on ImageNet-1k.
Hi @sanyalsunny111, you can try this script:
python -m torch.distributed.launch --nproc_per_node 8 main.py --cfg configs/1k/tiny_vit_21m.yaml --data-path ./ImageNet --batch-size 128 --opts DISTILL.TEACHER_LOGITS_PATH ./teacher_logits_1k AUG.MIXUP 0.8 AUG.CUTMIX 1.0 DATA.DATASET imagenet TRAIN.EPOCHS 300 DISTILL.LOGITS_TOPK 10
Just a quick question where the best checkpoints and training logs will be saved?
Hi @sanyalsunny111 ,
The checkpoint and log will be saved in the folder ./output
by default. You can change it by adding the command --output xxxx
when running the script.
Hey @wkcn could you please share your code for the Linear probe with various datasets as shown in Table 5 of the paper?
Hi @sanyalsunny111 , please refer to moco-v3 and Cross-Domain Few-Shot Learning (CD-FSL) Benchmark.
Hi @wkcn, I have used Linear Probe and a few shot codes from moco-v3 and CD-FSL, but it's not matching your results on Table 5. Is it possible for you to share your codes for the Linear probing and Few shot?
Could you please extend the date? Thanks a lot !
Hi @HaoWuSR , the date has been extended.
Hi @wkcn can you please extend the date?
Hi @BrendanCReidy, thanks for your attention to our work! The new link:
azcopy cp "https://tracking2019.blob.core.windows.net/tinyvit-teacher-logits/clip_224_22k_top100_logits_bs128/?sv=2020-04-08&st=2023-01-26T03%3A00%3A21Z&se=2023-02-09T03%3A00%3A00Z&sr=c&sp=rl&sig=lVTekKcg9SAvzF6AmyGJTIv%2FXNx42XLLqSYSfpxmWLY%3D" ./ --recursive
Hi @wkcn can you please extend the date?
HI @Andrewymd , thanks for your attention to our work! Here is the new link. The storage size of the teacher logits (clip_22k) is 499 GB.
Please install azcopy (https://learn.microsoft.com/en-us/azure/storage/common/storage-use-azcopy-v10) before downloading the teacher logits.
azcopy copy "https://hopengscus7387599778.blob.core.windows.net/tinyvit-teacher-logits/clip_224_22k_top100_logits_bs128/?sv=2021-08-06&se=2023-09-14T05%3A49%3A17Z&sr=c&sp=rl&sig=8HyBKYcLikVGtunLnTXgmtn8Ej0JiQsZt%2BCbexC6kfQ%3D" "./" --recursive
Hi @wkcn can you please extend the date? Thanks for your great work~
Hi @jotoy , here is the new download command.
azcopy copy "https://hopengscus7387599778.blob.core.windows.net/tinyvit-teacher-logits/clip_224_22k_top100_logits_bs128/?sv=2021-08-06&st=2023-10-30T16%3A30%3A11Z&se=2023-11-29T16%3A30%3A00Z&sr=c&sp=rl&sig=MuAQWkYvVfD8q4YEKH2BdjdFoHR5ZkpKlMIOJlt2diM%3D" "./" --recursive
Thanks for your attention to our work!
Hi @wkcn can you please extend the date? Thank you very much.
Hi @wkcn, another question, since all of the 90epochs logits are too huge, whether can I train the TinyViT using only the logics of epoch 90? Thanks!
@maybeliuchuan Thanks for your attention to our work!
Sorry that I could not extend the date. The logits can be reproduced by the teacher model CLIP-ViT-Large/14-22k on ImageNet-21k.
An epoch may be not enough on ImageNet-21k. You can try to save the teacher logits on ImageNet-1k. Here is the related tutorial: https://github.com/microsoft/Cream/blob/main/TinyViT/docs/SAVE_TEACHER_LOGITS.md
Dear Authors,
Very impressive work. For reproducibility purposes could you please share the teacher logits files for all the teachers shown in this paper?