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Hello, I went to test.py to generate a visualization of the anomaly localization after the training, following the closed way that others have asked you before, and I got the following error.What is t…
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Hi, thanks for your great work!
It is known that CLIP style contrast loss requires huge global batch sizes (e.g. 32k). I'd like to know if this is a critical issue in your training and the global bat…
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Hello, i am following your paper
your reference `[16] X. Gu, T.-Y. Lin, W. Kuo, and Y. Cui, “Zero-shot detection via vision and language knowledge distillation,” arXiv preprint arXiv:2104.13921,` i…
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https://github.com/jl749/knowledge-distillation-pytorch/blob/4a7c13d090554961f04b1b5f4ecc324cdca94d66/mnist/distill_mnist.py#L96-L97
 the authors find the optimal number of blocks to be 36. It has the minimal increase in latency and great increase in performance. So we need to…
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# 論文概要
様々なハードウェアやノイズレベルに対しQNN設計を可能にする、近似合成によるQNNの知識蒸留。層数を減らし異なるゲートセットを持つ新しいQNNを、ゼロから学習することなく作成できる。回路層を71.4%削減しても16.2%の精度向上を達成した。
# 論文を理解する上で重要な図など
# 論文リンク
[https://arxiv.org/abs/…
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Hi,
I find that after finishing knowledge distillation, the checkpoint file is very huge I get, so I think the checkpoint file include the student model and the teacher model. But when we deploy the …
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The error is following:
File "D:\PyCharm_workspace\KD\Knowledge-Distillation-via-ND-main\CIFAR\ReviewKD++\utils.py", line 62, in project_center
loss += 1 - torch.dot(s, e_c) / max_norm
RuntimeE…