Home: https://pypi.org/project/pytorch-lightning/
Package license: Apache-2.0
Feedstock license: BSD-3-Clause
Summary: PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.
Lightning is a way to organize your PyTorch code to decouple the science code from the engineering. It's more of a style-guide than a framework.
In Lightning, you organize your code into 3 distinct categories:
- Research code (goes in the LightningModule).
- Engineering code (you delete, and is handled by the Trainer).
- Non-essential research code (logging, etc. this goes in Callbacks).
Although your research/production project might start simple, once you add things like GPU AND TPU training, 16-bit precision, etc, you end up spending more time engineering than researching. Lightning automates AND rigorously tests those parts for you.
Overall, Lightning guarantees rigorously tested, correct, modern best practices for the automated parts.
- https://pytorch-lightning.readthedocs.io/en/latest
- https://pytorch-lightning.readthedocs.io/en/stable
All platforms: |
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Name | Downloads | Version | Platforms |
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Installing pytorch-lightning
from the conda-forge
channel can be achieved by adding conda-forge
to your channels with:
conda config --add channels conda-forge
conda config --set channel_priority strict
Once the conda-forge
channel has been enabled, pytorch-lightning
can be installed with conda
:
conda install pytorch-lightning
or with mamba
:
mamba install pytorch-lightning
It is possible to list all of the versions of pytorch-lightning
available on your platform with conda
:
conda search pytorch-lightning --channel conda-forge
or with mamba
:
mamba search pytorch-lightning --channel conda-forge
Alternatively, mamba repoquery
may provide more information:
# Search all versions available on your platform:
mamba repoquery search pytorch-lightning --channel conda-forge
# List packages depending on `pytorch-lightning`:
mamba repoquery whoneeds pytorch-lightning --channel conda-forge
# List dependencies of `pytorch-lightning`:
mamba repoquery depends pytorch-lightning --channel conda-forge
conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.
A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge Anaconda-Cloud channel for Linux, Windows and OSX respectively.
To manage the continuous integration and simplify feedstock maintenance
conda-smithy has been developed.
Using the conda-forge.yml
within this repository, it is possible to re-render all of
this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender
.
For more information please check the conda-forge documentation.
feedstock - the conda recipe (raw material), supporting scripts and CI configuration.
conda-smithy - the tool which helps orchestrate the feedstock.
Its primary use is in the construction of the CI .yml
files
and simplify the management of many feedstocks.
conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)
If you would like to improve the pytorch-lightning recipe or build a new
package version, please fork this repository and submit a PR. Upon submission,
your changes will be run on the appropriate platforms to give the reviewer an
opportunity to confirm that the changes result in a successful build. Once
merged, the recipe will be re-built and uploaded automatically to the
conda-forge
channel, whereupon the built conda packages will be available for
everybody to install and use from the conda-forge
channel.
Note that all branches in the conda-forge/pytorch-lightning-feedstock are
immediately built and any created packages are uploaded, so PRs should be based
on branches in forks and branches in the main repository should only be used to
build distinct package versions.
In order to produce a uniquely identifiable distribution:
- If the version of a package is not being increased, please add or increase
the
build/number
. - If the version of a package is being increased, please remember to return
the
build/number
back to 0.