tensorflow 使用多塊GPU同時訓練多個模型
阿新 • • 發佈:2019-01-08
轉自:http://stackoverflow.com/questions/34775522/tensorflow-mutiple-sessions-with-mutiple-gpus
TensorFlow will attempt to use (an equal fraction of the memory of) all GPU devices that are visible to it. If you want to run different sessions on different GPUs, you should do the following.
- Run each session in a different Python process.
-
Start each process with a different value for the
CUDA_VISIBLE_DEVICES
environment variable. For example, if your script is calledmy_script.py
and you have 4 GPUs, you could run the following:$ CUDA_VISIBLE_DEVICES=0 python my_script.py # Uses GPU 0. $ CUDA_VISIBLE_DEVICES=1 python my_script.py # Uses GPU 1. $ CUDA_VISIBLE_DEVICES=2,3 python my_script.py # Uses GPUs 2 and 3.
Note the GPU devices in TensorFlow will still be numbered from zero (i.e.
"/gpu:0"
etc.), but they will correspond to the devices that you have made visible withCUDA_VISIBLE_DEVICES
.