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There seems to be a inconsistency in the behavior of `groupe.prune()` when we provide it the `pruning_idxs` as an argument vs when updating the group with `group = self.DG.get_pruning_group(module, pr…
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the code logic in the #371 line of channel_pruning_env.py is missing one line code: self.shared_idx.append(share_group) should be added after the for loop.
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Hi @VainF ! Thank you for your work, but I have some strange problems:
After pruning on my own model, the weight of the model does not match any more.
(RuntimeError: Given groups=1, weight of size […
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Dear @liuzhuang13,
I guess we should prune some channel of subsequent conv layer' kernels after pruning current layer. Am I right?
So I can not figure out how to slim residual block using your m…
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Hello, I see from your paper that you used PAGCP on the NYUv2 dataset, but in the code here you only have implementation for VOC and COCO, is it possible to get the implementation for NYUv2? If not, a…
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**Describe the bug**
A clear and concise description of what the bug is.
I ran two distinct experiments, one on uniform quantization, and one on channel pruning with the same resnet model, however, …
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Hi @PengyiZhang , thank you for your repo.
I have a question though.
Now I have trained a yolov3 model on my own dataset. I want to know, what should I do to prune this model? Do have to 'spars…
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Hi, thanks for this very nice project. It's really polished and takes a lot of complexity out of yt-dlp, which is great.
I tried running yark on a couple of large-ish channels (10.000s of videos), …
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CI on #1544 failed with the following, implying the test is not stable:
```
Running `/Users/runner/work/rust-lightning/rust-lightning/target/debug/deps/lightning_background_processor-7b9bd7…
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following this toturial(https://github.com/quic/aimet/blob/develop/Examples/torch/compression/channel_pruning.py), a big model has been pruned. here, comress.py is my script, and compress_model.pt is…