PyTorch is an open source machine learning framework with GPU acceleration and deep neural networks that is based on the automatic differentiation in the Torch library of tensors.
OSC does not provide general access to PyTorch. However, we are available to assist with the configuration of local individual/research-group installations on all our clusters. If you have any questions, please contact OSC Help.
Installing PyTorch Locally
Here is a quick recipe that was used in February 2022 to install a GPU enabled version compatible with the CUDA drivers on the clusters at that time:
module load python/3.7-2019.10 cuda/11.1.1
; module list ;
conda create -n pytorch
; source activate pytorch
; pip install -t ~/local/pytorch torch==1.10.2+cu111 torchvision==0.11.3+cu111 -f https://download.pytorch.org/whl/cu111/torch_stable.html
This uses a local install directory hierarchy described here and can be tested via:
module load python/3.7-2019.10 cuda/11.1.1 ; module list ; source activate pytorch
Here is an older recipe with explanations.
Create a local python environment (e.g., pytorch-test) for Pytorch installation:
Load a python module:
module load python/3.6-conda5.2
Create a local python environment (e.g., pytorch-test) for Pytorch installation:
conda create -n pytorch-test python=3.6 anaconda
Activate the environment:
source activate pytorch-test
Install Pytorch:
pip install torch torchvision
Please refer here if you want a different version of the Pytorch.
Please follow this link for more information.
Feel free to contact OSC Help if you have any issues with installation.
Publisher/Vendor/Repository and License Type
https://pytorch.org, Open source.
Usage on Owens
Usage on Owens
Batch Usage on Owens
Batch jobs can request multiple nodes/cores and compute time up to the limits of the OSC systems. Refer to Queues and Reservations for Owens, and Scheduling Policies and Limits for more info. In particular, Pytorch should be run on a GPU-enabled compute node.
An Example Batch Script Templte
Below is an example batch script (job.pbs
) for using PyTorch.
Contents of job.pbs
#PBS -N pytorch #PBS -l nodes=1:ppn=28:gpus=1:default #PBS -l walltime=30:00 #PBS -j oe #PBS -S /bin/bash #PBS -A yourprojectID cd $PBS_O_WORKDIR module load python/3.6 cuda source activate your-local-python-environment-name python your-pytorch-script.py
In order to run it via the batch system, submit the job.pbs
file with the following command:
qsub job.pbs