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37 lines
1.3 KiB
Markdown
37 lines
1.3 KiB
Markdown
# Parital FC
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Pytorch is currently still a preview version. There is a 5 thousandth difference between the sampling of 0.1 and the paper.
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**If you want to reproduce the accuracy in the paper, it is strongly recommended to use mxnet first. **
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All experiments in the paper are done by mxnet.
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Pytorch 目前是还是预览版本，模型并行是没问题的，但是0.1的采样**暂时无法使用**，
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**如果要使用采样(复现论文中的精度)，强烈建议优先使用mxnet, 所有论文的实验均是mxnet完成的**。
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我们会马上修复这个bug。
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Insightface 社区需要大家一起贡献才会变得更好，欢迎大家提交Pull Request.
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## How to run
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cuda=10.1
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pytorch==1.6.0
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pip install -r requirement.txt
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```shell
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bash run.sh
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```
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使用 `bash run.sh` 这个命令运行。
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## Citation
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If you find Partial-FC or Glint360K useful in your research, please consider to cite the following related paper:
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[Partial FC](https://arxiv.org/abs/2010.05222)
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```
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@inproceedings{an2020partical_fc,
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title={Partial FC: Training 10 Million Identities on a Single Machine},
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author={An, Xiang and Zhu, Xuhan and Xiao, Yang and Wu, Lan and Zhang, Ming and Gao, Yuan and Qin, Bin and
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Zhang, Debing and Fu Ying},
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booktitle={Arxiv 2010.05222},
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year={2020}
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}
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```
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