Replies: 1 comment 1 reply
-
我们已经在Paddle内部实现了类似torch-quiver的后端,具体可以看https://github.com/PaddlePaddle/Paddle/tree/develop/python/paddle/geometric 下的一些相关内容。目前PGL可以类似torch-quiver一样支持单机多卡的训练,近期我们会在PGL库中集成相关的例子(如Graphsage),可以关注一下。 |
Beta Was this translation helpful? Give feedback.
1 reply
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
Uh oh!
There was an error while loading. Please reload this page.
-
pgl是否可以类似torch那样,使用torch.multiprocessing.spwan来进行单机多卡的训练 ,我准备实现paddle后端的torch-quiver(https://github.com/quiver-team/torch-quiver),因为在torch后端的时候,可以在spwan的args中加入自定义的类https://github.com/quiver-team/torch-quiver/blob/main/examples/multi_gpu/pyg/reddit/dist_sampling_ogb_reddit_quiver.py#L146
,paddle后端应该怎样处理呢,我看paddle的源码里,只有paddle.distributed支持spwan,paddle的multiprocessing,不似torch,只有reductions,没有其他的内容。
请问我该如何使用paddle实现https://github.com/quiver-team/torch-quiver/blob/main/examples/multi_gpu/pyg/reddit/dist_sampling_ogb_reddit_quiver.py#L146
的分布式训练呢
Beta Was this translation helpful? Give feedback.
All reactions