Installing condor_pytorch
Requirements
Condor requires the following software and packages:
PyPI
You can install the latest stable release of condor_pytorch directly from Python's package index via pip by executing the following code from your command line:
pip install condor-pytorch
The dependencies can be pip installed also using the included requirements.txt:
pip install -r requirements.txt
Latest GitHub Source Code
You want to try out the latest features before they go live on PyPI? Install the condor_pytorch dev-version latest development version from the GitHub repository by executing
pip install git+git://github.com/GarrettJenkinson/condor_pytorch.git
Alternatively, you download the package manually from GitHub via the Dowload ZIP button, unzip it, navigate into the package directory, and execute the following command:
python setup.py install
Docker
If one does not wish to install things locally, running a docker container can make it simple to run Condor pytorch.
We provide Dockerfile's to help get up and started quickly with condor_pytorch.
The cpu image can be built and ran as follows, with tutorial jupyter notebooks
built in.
# Create a docker image, only done once
docker build -t cpu_pytorch -f cpu.Dockerfile ./
# run image to serve a jupyter notebook
docker run -it -p 8888:8888 --rm cpu_pytorch
# how to run bash inside container (with python that will have deps)
docker run -u $(id -u):$(id -g) -it -p 8888:8888 --rm cpu_pytorch bash
An NVIDIA based gpu optimized container can be built and run as follows (without interactive ipynb capabilities).
# only needs to be built once
docker build -t gpu_pytorch -f gpu.Dockerfile ./
# use the image after building it
docker run -it -p 8888:8888 --rm gpu_pytorch