ignite
code-generator
ignite | code-generator | |
---|---|---|
3 | 1 | |
4,458 | 38 | |
0.3% | - | |
8.7 | 7.4 | |
1 day ago | 23 days ago | |
Python | Vue | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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
-
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.
-
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.
-
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.
code-generator
-
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.
What are some alternatives?
torch-metrics - Metrics for model evaluation in pytorch
BigGAN-PyTorch - The author's officially unofficial PyTorch BigGAN implementation.
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.
traingenerator - 🧙 A web app to generate template code for machine learning
prometheus_flask_exporter - Prometheus exporter for Flask applications
receptive_field_analysis_toolbox - A toolbox for receptive field analysis and visualizing neural network architectures
pymetrix - A simple Plug and Play Library for getting analytics. See website for docs.
xla - Enabling PyTorch on XLA Devices (e.g. Google TPU)
gloo - Collective communications library with various primitives for multi-machine training.
idist-snippets
why-ignite - Why should we use PyTorch-Ignite ?
NCCL - Optimized primitives for collective multi-GPU communication