PyTorch
Contents
PyTorch#
PyTorch is an end-to-end machine learning framework. PyTorch enables fast, flexible experimentation and efficient production through a user-friendly front-end, distributed training, and ecosystem of tools and libraries.
The main method of distribution for PyTorch is via Conda, with Open-CE providing a simple method for installing multiple machine learning frameworks into a single conda environment.
The upstream Conda and pip distributions do not provide ppc64le pytorch packages at this time.
Installing via Conda#
With a working Conda installation (see Installing Miniconda) the following instructions can be used to create a Python 3.9 conda environment named torch with the latest Open-CE provided PyTorch:
Note
Pytorch installations via conda can be relatively large. Consider installing your miniconda (and therfore your conda environments) to the /nobackup file store.
# Create a new conda environment named torch-env within your conda installation
conda create -y --name torch-env python=3.8
# Activate the conda environment
conda activate torch-env
# Add the OSU Open-CE conda channel to the current environment config
conda config --env --prepend channels https://ftp.osuosl.org/pub/open-ce/current/
# Also use strict channel priority
conda config --env --set channel_priority strict
# Install the latest available version of PyTorch
conda install -y pytorch
In subsequent interactive sessions, and when submitting batch jobs which use PyTorch, you will then need to re-activate the conda environment.
For example, to verify that PyTorch is available and print the version:
# Activate the conda environment
conda activate torch-env
# Invoke python
python3 -c "import torch;print(torch.__version__)"
Installation via the upstream Conda channel is not currently possible, due to the lack of ppc64le or noarch distributions.
Further Information#
For more information on the usage of PyTorch, see the Online Documentation.