Trying to do inference on a machine with an A100 GPU. Here's my cog file:
image: "myimage"
build:
gpu: true
python_version: "3.8"
cuda: "11.3"
python_packages:
- "transformers==4.15.0"
- "torch==1.10.1"
- "ray[serve]==1.5.0"
- "kfserving==0.6.1"
When I do sudo cog run python model.py I get the following error:
/root/.pyenv/versions/3.8.12/lib/python3.8/site-packages/torch/cuda/__init__.py:106: UserWarning:
NVIDIA A100-PCIE-40GB with CUDA capability sm_80 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
If you want to use the NVIDIA A100-PCIE-40GB GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
> /src/model.py(24)predict()
-> output_ids = self.model.generate(input_ids.cuda())
So apparently my CUDA installation is missing some capabilities. Looking at stack overflow, it seems like doing
pip3 install torch==1.10.1+cu113 -f https://download.pytorch.org/whl/cpu/torch_stable.html
might fix that problem? But I can't pin 1.10.1+cu113 since cog doesn't allow us to specify custom pip archives via pip -f
Trying to do inference on a machine with an A100 GPU. Here's my cog file:
When I do
sudo cog run python model.pyI get the following error:So apparently my CUDA installation is missing some capabilities. Looking at stack overflow, it seems like doing
pip3 install torch==1.10.1+cu113 -f https://download.pytorch.org/whl/cpu/torch_stable.htmlmight fix that problem? But I can't pin
1.10.1+cu113since cog doesn't allow us to specify custom pip archives viapip -f