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### Describe the issue
In all networks module, the parameters handled as input lists have an assertion for the length of the list, but assertions are not a good idea, they should be replaced by raise…
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https://arxiv.org/abs/1605.07146
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# Dilated Residual Networks #
- Author: Fisher Yu, Vladlen Koltun, Thomas Funkhouser
- Origin: https://www.cs.princeton.edu/~funk/drn.pdf
- Related:
- [论文笔记——CVPR 2017 Dilated Residual Network…
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related paper
|摘要|
|---|
|Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance. However, each fraction of a percent of improved acc…
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- https://arxiv.org/abs/2102.07870v2
- 2021
バックプロパゲーションを用いた深い残差ニューラルネットワーク(ResNets)の学習には、ネットワークの深さに応じて線形に増加するメモリコストがかかります。
この問題を回避する方法として、可逆的なアーキテクチャを使用することが挙げられる。
本論文では、モーメンタム項を追加することで、ResNetの順…
e4exp updated
3 years ago
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Hi Avanti and others,
Thank you for the great tool! I would like to use your package to compute the feature contribution for the residual network, however it seems that this type of layers is not s…
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When run
hidden_states, residual = fused_add_norm_fn(
hidden_states if residual is None else self.drop_path(hidden_states),
self.norm.weight,
self.norm.bias,
residual=residual,
prenorm=True,
re…
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how about the experiment details and results on Residual-Attention-Network?
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Hi, I wanna test the pre-trained model performance, but I meet some problems. I would appreciated if you can help me!
The First problem is, **ModuleNotFoundError: No module named 'data.single_datas…
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Similar to #74, I'm in the process of swapping in optimistix for a previous solver. The system I'm solving is a relatively small chemical network with mass balance (so think law of mass action plus co…