Good morning!
I have very simple configuration problem that I am in the process of googling and troubleshooting. I have installed scVI-tools via conda as shown here Installation — scvi-tools
conda create -n scvi-env python=3.7
source activate scvi-env
conda install scvi-tools -c bioconda -c conda-forge
and scVI works fine. BUT it says there is no GPU available. I am currently going through separate PyTorch documents to see if I need some additional config. The issue is almost certainly my config and not related to scVI directly. However, since everyone here has experience setting this up, I figured it wouldnt hurt to ask in this forum about any troubleshooting steps you might know that I as a new scVI user might be missing.
Thanks in advance for any tips or tricks! I will update this thread as I try different things I find via google.
okay so after reinstalling PyTorch in the scivi-env , i still get
GPU available: False, used: False
TPU available: False, using: 0 TPU cores
I installed PyTorch in the environment with
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
I am on Ubuntu 20.04 with a GeForce RTX 2080 Ti
Thank you again in advance for tips and tricks…
Hi, getting a CUDA environment working can be frustrating…
Just a quick check, does the nvidia-smi command in the shell work and return some stats about your GPU?
Thank you Valentine for joining me on my GPU PyTorch adventure!
yes nvidia-smi does indeed work and return some information. I am going to copy and paste the return results as they don’t all mean anything to me per-say
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.80 Driver Version: 460.80 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 208... Off | 00000000:23:00.0 On | N/A |
| 33% 53C P0 66W / 250W | 1168MiB / 11016MiB | 2% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 2754 G /usr/lib/xorg/Xorg 90MiB |
| 0 N/A N/A 3700 G /usr/lib/xorg/Xorg 633MiB |
| 0 N/A N/A 3839 G /usr/bin/gnome-shell 151MiB |
| 0 N/A N/A 6039 G ...AAAAAAAA== --shared-files 30MiB |
| 0 N/A N/A 6704 G /usr/lib/firefox/firefox 150MiB |
| 0 N/A N/A 6857 G /usr/lib/firefox/firefox 3MiB |
| 0 N/A N/A 6867 G /usr/lib/firefox/firefox 2MiB |
| 0 N/A N/A 6888 G /usr/lib/firefox/firefox 2MiB |
| 0 N/A N/A 6951 G /usr/lib/firefox/firefox 2MiB |
| 0 N/A N/A 6974 G /usr/lib/firefox/firefox 2MiB |
| 0 N/A N/A 7004 G /usr/lib/firefox/firefox 2MiB |
| 0 N/A N/A 13544 G /usr/lib/rstudio/bin/rstudio 51MiB |
| 0 N/A N/A 14300 G gnome-control-center 3MiB |
+-----------------------------------------------------------------------------+
further further update:
I ran the PyTorch commands to ping the GPU availability, and by raw in python it works
(base) UserNameHidden :~/Desktop$ python
Python 3.8.5 (default, Sep 4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>>
>>> torch.cuda.is_available()
True
>>> torch.cuda.device_count()
1
>>> torch.cuda.get_device_name(0)
'GeForce RTX 2080 Ti'
>>> torch.cuda.get_device_properties(0)
_CudaDeviceProperties(name='GeForce RTX 2080 Ti', major=7, minor=5, total_memory=11016MB, multi_processor_count=68)
EDIT: I just redid it while in scvi-env and not base , just to make sure installation had access… same results… but still when I run model$train() its saying no GPU
I have solved the problem , my answer was here → scvi.model.SCVI.train — scvi-tools
by default in the function use_gpu is set to false , you have to pass TRUE to enable… i feel like an idiot 
Well the default is None which uses the gpu if it’s available, so I think something else might have happened?
@LabCoatNomad glad you solved your install problem.
I saw you are using CUDA 11.2, so just wanted to leave a note here in case it helps other people. I actually also had trouble getting the GPU to work torch tensors it, but in my case I found it to be a pytorch issue: Apparently pytorch doesn’t yet support CUDA 11.2 but after trying a bunch of things it magically worked when I tried installing pytorch from the nightly builds.
1 Like
on my machine can confirm model$train() returns GPU available: False, used: False , but when I do model$train(use_gpu = TRUE) i get GPU available: True, used: True , it could be something weird with my config or setup, but all my steps of what I have done are above and this is how its working… * shrug * dont know why , but happy it works =)
Weird… if it works it works…