OS: Ubuntu 20.04
GPU: RTX 3090
cog version: 0.0.20
With this minimal cog.yaml I run into problems.
build:
gpu: true
cuda: "11.3"
python_version: "3.8"
python_packages:
- "torch==1.10.2"
- "torchvision==0.11.3"
The image builds without error, just a warning about being unsure whether cuda and pytorch match. However, this matches the pytorch recommended installation versions as of 2022/02/22 which is to run pip3 install torch==1.10.2+cu113 torchvision==0.11.3+cu113 torchaudio==0.10.2+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html.
However, once the image is built I cannot actually use the GPU, the issue being that running:
cog run python -c "import torch; print(torch.__version__)"
gives me "1.10.2+cu102", and cuda 10.2 is not compatible with the architecture of the 3090.
To get around this I added the command pytorch recommends above directly to the run section of the cog.yaml, which works but is very clunky.
OS: Ubuntu 20.04
GPU: RTX 3090
cog version: 0.0.20
With this minimal cog.yaml I run into problems.
The image builds without error, just a warning about being unsure whether cuda and pytorch match. However, this matches the pytorch recommended installation versions as of 2022/02/22 which is to run
pip3 install torch==1.10.2+cu113 torchvision==0.11.3+cu113 torchaudio==0.10.2+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html.However, once the image is built I cannot actually use the GPU, the issue being that running:
cog run python -c "import torch; print(torch.__version__)"gives me "1.10.2+cu102", and cuda 10.2 is not compatible with the architecture of the 3090.
To get around this I added the command pytorch recommends above directly to the
runsection of the cog.yaml, which works but is very clunky.