Weirui Ye
Weirui Ye
Cora: 81.2 Citeseer: 68.7 Pubmed: 75.6
When data is limited, the reward function can be trained more easily by clipping rewards. That's the reason for reward clipping. As for why applying value transformation, we choose the...
A larger ratio of reanalyzing can make training more efficient. Actually, there is no significant difference between 99% of reanalyzing targets and 100% of reanalyzing targets since 99% and 100%...
It seems you could try more cpu and gpu actors, such as `--cpu_actor 14 --gpu_actor 20`. Since you have 4 RTX6000 and each RTX6000 has more than 20GB of memory,...
It seems that only one GPU is allocated. Have you set `--num_gpus 4 --num_cpus 28`? By the way, if you find CPU resources are not enough, you can set `@ray.remote(num_cpus=0.5)`.
I noticed that you set `--gpu_actor 4` here. That's why only one GPU is in use (each reanalyze gpu actor takes 0.125 gpu, 4 x 0.125 = 0.5). Could you...
> > > It seems that only one GPU is allocated. Have you set `--num_gpus 4 --num_cpus 28`? > > > By the way, if you find CPU resources are...
It is possible when the remote functions are executed fast. Maybe you can try the remote class. ``` import os import ray import time ray.init(num_gpus=4) @ray.remote(num_gpus=1) class Test(): def __init__(self):...
Thank you for your comments. Here we scatter the actions to planes to ensure the shape is the same as the shape of the feature plane (eg: feature is B...
I'm afraid that we have no time for this. If you are interested in, you can have a try : )