We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
需要什么样的机器配置,才能训练mag240M数据的metapath2vec,有接近3亿个节点,embeding非常大,训练速度很慢
The text was updated successfully, but these errors were encountered:
而且显存占用也很大,batch=1都难以训练
Sorry, something went wrong.
metapath2vec的训练建议使用分布式CPU模式。
我们已经将MAG240M 训练好的 m2v_embedding 提供了云盘下载的地址。具体看下面链接里面,m2v embedding部分 https://github.com/PaddlePaddle/PGL/tree/main/examples/kddcup2021/MAG240M/r_unimp
谢谢给的预训练特征,问一下分布式cpu模式,用的什么机器配置,训练了多久
我们用MPI集群训练的,为了追求速度20台机一起训,因为训这套向量的时间已经比较久了,花的时间记录没了。你也可以按照 Graph4Rec里面提供的配置去训,只要机器内存加起来能超过向量所需的内存,应该能跑起来了。
No branches or pull requests
需要什么样的机器配置,才能训练mag240M数据的metapath2vec,有接近3亿个节点,embeding非常大,训练速度很慢
The text was updated successfully, but these errors were encountered: