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This repository has been archived by the owner on Aug 30, 2023. It is now read-only.
Hello,
As the title suggests, I am unable to train this model on multiple gpu configuration. I am trying to train it on 4 RTX 2080 Ti.
It loads up the model only on the 1st GPU utilizing a memory of around 10.5 GB/11 GB
For the remaining GPU's, it is only utilizing a memory of 155 MB/11 GB.
Also, the training speed is independent of the number of GPU's selected by me using CUDA_VISIBLE_DEVICES. So, apparently it is only using the 1st GPU.
I tried diving in the code to find out the exact function multi_gpu_model, but everything seemed fine to me.
So, can you confirm or tell me how to train this implementation over multiple GPU's?
The text was updated successfully, but these errors were encountered:
Hello,
As the title suggests, I am unable to train this model on multiple gpu configuration. I am trying to train it on 4 RTX 2080 Ti.
It loads up the model only on the 1st GPU utilizing a memory of around 10.5 GB/11 GB
For the remaining GPU's, it is only utilizing a memory of 155 MB/11 GB.
Also, the training speed is independent of the number of GPU's selected by me using
CUDA_VISIBLE_DEVICES
. So, apparently it is only using the 1st GPU.I tried diving in the code to find out the exact function multi_gpu_model, but everything seemed fine to me.
So, can you confirm or tell me how to train this implementation over multiple GPU's?
The text was updated successfully, but these errors were encountered: