ignite
gloo
| ignite | gloo | |
|---|---|---|
| 3 | 2 | |
| 4,458 | 1,140 | |
| 0.4% | 0.7% | |
| 8.7 | 8.0 | |
| 5 days ago | 9 days ago | |
| Python | C++ | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ignite
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Introducing PyTorch-Ignite's Code Generator v0.2.0
Along with the PyTorch-Ignite 0.4.5 release, we are excited to announce the new release of the web application for generating PyTorch-Ignite's training pipelines. This blog post is an overview of the key features and updates of the Code Generator v0.2.0 project release.
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Distributed Training Made Easy with PyTorch-Ignite
PyTorch-Ignite's ignite.distributed (idist) submodule introduced in version v0.4.0 (July 2020) quickly turns single-process code into its data distributed version.
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Introduction to PyTorch-Ignite
More details about distributed helpers provided by PyTorch-Ignite can be found in the documentation. A complete example of training on CIFAR10 can be found here.
gloo
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Releasing Gloo 0.4.0
These are two separate libraries that do very different things but share the same name. They are also written in two separate languages. That is a sizable gap between them, and reusing names happens often with libraries. Gloo (rust-wasm, this post) is also not new. Though, relative to Gloo (Go, solo-io), it is newer. But, there is also a Github repo even older than Gloo (solo-io): https://github.com/facebookincubator/gloo. As well, even if these were for some odd reason all about wasm, none of them are actually that popular. solo-io Gloo has the most stars (though that isn't the best metric of popularity, since it is relative to the community that actually uses it), but 3k simply isn't that much. There is certainly a good argument to look down on libraries that reuse popular library names, but this isn't really the case here. Both started not too long after each other (solo-io would not have most of the stars it currently has when Gloo-Rust started), are in separate languages (thus separate communities), and do very separate things.
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Distributed Training Made Easy with PyTorch-Ignite
backends from native torch distributed configuration: nccl, gloo, mpi.
What are some alternatives?
torch-metrics - Metrics for model evaluation in pytorch
NCCL - Optimized primitives for collective multi-GPU communication
image-similarity-measures - :chart_with_upwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
ompi - Open MPI main development repository
prometheus_flask_exporter - Prometheus exporter for Flask applications
gloo - The Feature-rich, Kubernetes-native, Next-Generation API Gateway Built on Envoy
pymetrix - A simple Plug and Play Library for getting analytics. See website for docs.
why-ignite - Why should we use PyTorch-Ignite ?
xla - Enabling PyTorch on XLA Devices (e.g. Google TPU)
idist-snippets
code-generator - Web Application to generate your training scripts with PyTorch Ignite