light-the-torch

package
code
tests

With each release of a PyTorch distribution (torch, torchvision, torchaudio, torchtext) the wheels are published for combinations of different Python versions, platforms, and computation backends (CPU, CUDA). Unfortunately, a differentation based on the computation backend is not supported by PEP 440 . As a workaround the computation backend is added as a local specifier. For example

torch==1.5.1+<computation backend>

Due to this restriction only the wheels of the latest CUDA release are uploaded to PyPI and thus easily pip install able. For other CUDA versions or the installation without CUDA support, one has to resort to manual version specification:

pip install -f https://download.pytorch.org/whl/torch_stable.html torch==1.5.1+<computation backend>

This is especially frustrating if one wants to install packages that depend on one or several PyTorch distributions: for each package the required PyTorch distributions have to be manually tracked down, resolved, and installed before the other requirements can be installed.

light-the-torch offers a small CLI based on pip to install the PyTorch distributions from the stable releases. Similar to the Python version and platform, the computation backend is auto-detected from the available hardware preferring CUDA over CPU.

Installation

The latest published version can be installed with

pip install light-the-torch

The latest, potentially unstable development version can be installed with

pip install git+https://github.com/pmeier/light-the-torch

Usage

light-the-torch is invoked with its shorthand ltt

$ ltt --help

usage: ltt [-h] [-V] [--computation-backend COMPUTATION_BACKEND]
           [--full-install] [--install-cmd INSTALL_CMD] [--no-install]
           [args [args ...]]

Install PyTorch distributions from the stable releases. The computation
backend is autodetected from the available hardware preferring CUDA over CPU.

positional arguments:
  args                  arguments passed to pip install. Required PyTorch
                        distributions are extracted and installed. Optional
                        arguments for pip install have to be seperated by '--'
                        (default: None)

optional arguments:
  -h, --help            show this help message and exit
  -V, --version         show version and exit (default: False)
  --computation-backend COMPUTATION_BACKEND
                        pin computation backend, e.g. 'cpu' or 'cu102'
                        (default: None)
  --full-install        install remaining requirements after PyTorch
                        distributions are installed (default: False)
  --install-cmd INSTALL_CMD
                        installation command. '{links}' is substituted for the
                        links. If present, '{opts}' is substituted for most
                        additional pip install options. Exceptions are -e /
                        --editable <path/url> and -r / --requirement <file>
                        (default: pip install {opts} {links})
  --no-install          print wheel links instead of installing (default:
                        False)

Example 1

ltt can be used to install PyTorch distributions without worrying about the computation backend:

$ ltt torch torchvision
[...]
Successfully installed future-0.18.2 numpy-1.19.0 pillow-7.2.0 torch-1.5.1+cu101 torchvision-0.6.1+cu101

Example 2

ltt extracts the required PyTorch distributions from the positional arguments:

$ ltt kornia
[...]
Successfully installed torch-1.5.0+cu101

Example 3

The --full-install option can be used as a replacement for pip install:

$ ltt --full-install kornia
[...]
Successfully installed future-0.18.2 numpy-1.19.0 torch-1.5.0+cu101
[...]
Successfully installed kornia-0.3.1

Example 4

The --no-install option can be used to pipe or redirect the PyTorch wheel links. For example, generating a requirements.txt file:

$ ltt --no-install torchaudio > requirements.txt
$ cat requirements.txt
https://download.pytorch.org/whl/cu101/torch-1.5.1%2Bcu101-cp36-cp36m-linux_x86_64.whl
https://download.pytorch.org/whl/torchaudio-0.5.1-cp36-cp36m-linux_x86_64.whl

Example 5

The --computation-backend option as well as the --platform and --python-version options from pip install can be used to disable the autodetection:

$ ltt \
  --no-install \
  --computation-backend cu92 \
  -- \
  --python-version 37 \
  --platform win_amd64 \
  torchtext
https://download.pytorch.org/whl/cu92/torch-1.5.1%2Bcu92-cp37-cp37m-win_amd64.whl
https://download.pytorch.org/whl/torchtext-0.6.0-py3-none-any.whl

Metadata

Release files for light-the-torch 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for light-the-torch 0.1.0
File	Size	Uploaded	Provenance
light_the_torch-0.1.0.tar.gz	14.5 kB	Jul 10, 2020	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for light-the-torch 0.1.0
File	Interpreter	ABI	Platform	Reset
light_the_torch-0.1.0-py3-none-any.whl 13.4 kB Jul 10, 2020 Without provenance	Python 3	none	any	Details

Total release size: 28.0 kB

Release files / light_the_torch-0.1.0.tar.gz

Download URL	light_the_torch-0.1.0.tar.gz
Size	14.5 kB
Tags	Source
SHA-256 checksum How to use checksums	`1a9c333851b6fc08eb97784311c2bc7547c93c280f14b406d646ec9d42c04f84`
BLAKE2b-256 checksum How to use checksums	`878522db05e6afbbee30549632dc4664c64aa62ff422646d9b3e2ea2095d86d9`
Upload date	Jul 10, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.1.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.6.10`

Release files / light_the_torch-0.1.0-py3-none-any.whl

Download URL	light_the_torch-0.1.0-py3-none-any.whl
Size	13.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`29d5eee3932261b3e8f12875682d6cfd51079597fb9e899dd2153110d2f4f69b`
BLAKE2b-256 checksum How to use checksums	`30581baf1300bf39e5ff04f2e894ae5d6d7394facbc82bf87a5e010009c19b19`
Upload date	Jul 10, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.1.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.6.10`

Security for light-the-torch 0.1.0

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.