https://github.com/hci-unihd/plant-seg
Install PlantSeg
conda create -n plant-seg -c pytorch -c conda-forge cudatoolkit=10.1 -c lcerrone -c abailoni -c cpape -c awolny pytorch nifty=1.0.9 plantseg
To install pytorch for a certain cudatoolkit version
conda install pytorch cudatoolkit=10.1 -c pytorch
plantseg --gui
To designate a certain cuda GPU device when run plant-seq with
CUDA_VISIBLE_DEVICES=0 plantseg --gui
To check cuda is available in pytorch
import torch
torch.cuda.is_available()
To check GPU usage
nvidia-smi -l 1
To check CUDA version
nvcc -V
How to run python code from Terminal in multiple sessions with multiple GPUs
1. set CUDA device
$ CUDA_VISIBLE_DEVICES=0 python test1.py # Uses GPU 0.
$ CUDA_VISIBLE_DEVICES=1 python test2.py # Uses GPU 1.
$ CUDA_VISIBLE_DEVICES=2,3 python test3.py # Uses GPUs 2 and 3.
or
2. add in python code
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]="0"
ref:
https://stackoverflow.com/questions/34775522/tensorflow-multiple-sessions-with-multiple-gpus
https://stackoverflow.com/questions/37893755/tensorflow-set-cuda-visible-devices-within-jupyter