Install PyTorch distributions from the latest wheels.
Project description
Note
This project is deprecated and will see no further development. It is superseded by light-the-torch .
Original README below.
Disclaimer
Neither this project (pytorch_wheel_installer) nor its author (Philip Meier) are affiliated with PyTorch in any way. PyTorch and any related marks are trademarks of Facebook, Inc.
pytorch_wheel_installer
Commandline utility and tox -plugin to install PyTorch distributions from the latest wheels. The computation backend (CPU, CUDA), the language version, and the platform are detected automatically but can be overwritten manually.
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Installation
The latest stable version can be installed with
pip install pytorch_wheel_installer
The latest potentially unstable version can be installed with
pip install git+https://github.com/pmeier/pytorch_wheel_installer
Usage
CLI
The CLI can be invoked by pytorch_wheel_installer or its shorthand pwi.
$ pwi --help
usage: pwi [-h] [-v] [-d DISTRIBUTION] [-b BACKEND] [-p PLATFORM]
[-l LANGUAGE] [-ni] [-ic INSTALL_CMD]
Install PyTorch from the latest wheels.
optional arguments:
-h, --help show this help message and exit
-v, --version Show version and exit.
-d DISTRIBUTION, --distribution DISTRIBUTION
PyTorch distribution e.g. 'torch', 'torchvision'.
Multiple distributions can be given as a comma-
separated list. Defaults to 'torch,torchvision'.
-b BACKEND, --backend BACKEND
Computation backend e.g. 'cpu' or 'cu102'. If not
given the backend is automatically detected from the
available hardware preferring CUDA over CPU.
-p PLATFORM, --platform PLATFORM
Platform e.g. 'linux', 'windows', 'macos', or 'any'.
Defaults to the platform that is used to run this.
-l LANGUAGE, --language LANGUAGE
Language implementation and version tag e.g. 'py3',
'cp36'. Defaults to the language version used to run
this.
-ni, --no-install If given, the selected wheels are written to STDOUT
instead of installed.
-ic INSTALL_CMD, --install-cmd INSTALL_CMD
Command that is used to install the wheels. Defaults
to 'pip install'
The --no-install option can be used to pipe or redirect the wheel links such as generating a requirements.txt file:
$ pwi --no-install > requirements.txt
$ cat requirements.txt
https://download.pytorch.org/whl/cu102/torch-1.5.1-cp36-cp36m-linux_x86_64.whl
https://download.pytorch.org/whl/cu102/torchvision-0.6.1-cp36-cp36m-linux_x86_64.whl
tox
$ tox --help
...
optional arguments:
...
--pytorch-install Install PyTorch from the latest wheels. (default:
False)
--pytorch-distribution DISTRIBUTION
PyTorch distribution e.g. 'torch', 'torchvision'.
Multiple distributions can be given as a
comma-separated list. Defaults to
'torch,torchvision'. (default: torch,torchvision)
--pytorch-backend BACKEND Computation backend e.g. 'cpu' or 'cu102'. If not
given the backend is automatically detected from
the available hardware preferring CUDA over CPU.
(default: None)
--pytorch-language LANGUAGE Language implementation and version tag e.g.
'py3', 'cp36'. Defaults to the language version
used to run this. (default: None)
--pytorch-platform PLATFORM Platform e.g. 'linux', 'windows', 'macos', or
'any'. Defaults to the platform that is used to
run this. (default: None)
...
$ tox --help-ini
pytorch_install <bool> default: False
Install PyTorch from the latest wheels.
pytorch_distribution <string> default: torch,torchvision
PyTorch distribution e.g. 'torch', 'torchvision'. Multiple distributions can be given
as a comma-separated list. Defaults to 'torch,torchvision'.
pytorch_backend <string> default: None
Computation backend e.g. 'cpu' or 'cu102'. If not given the backend is automatically
detected from the available hardware preferring CUDA over CPU.
pytorch_language <string> default: None
Language implementation and version tag e.g. 'py3', 'cp36'. Defaults to the language
version used to run this.
pytorch_platform <string> default: None
Platform e.g. 'linux', 'windows', 'macos', or 'any'. Defaults to the platform that is
used to run this.
If neither --pytorch-install nor pytorch_install = true is given, nothing is installed.
Python
To find the links to the wheels for a specific setup, the function find_links can be used from within Python:
from pytorch_wheel_installer import find_links
links = find_links(
distributions=("torch", "torchvision"),
backend="cpu",
language="py36",
platform="linux",
)
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