New features and bug fixes

Core

Various improvements in the core part of the library:

• Add epoch_bound parameter to RunningAverage (#488)

• Bug fixes with Confusion matrix, new implementation (#572) - BC breaking

• Added event_to_attr in register_events (#523)

• Added accumulative single variable metrics (#524)

• should_terminate is reset between runs (#525)

• to_onehot returns tensor with uint8 dtype (#571) - may be BC breaking

• Removable handle returned from Engine.add_event_handler() to enable single-shot events (#588)

• New documentation style 🎉

Distributed

We removed mnist distrib example as being misleading and provided distrib branch(XX/YY/2020: distrib branch merged to master) to adapt metrics for distributed computation. Code is working and is under testing. Please, try it in your use-case and leave us a feedback.

Now in Contributions module

• Added mlflow logger (#558)
• R-Squared Metric in regression metrics module (#496)
• Add tag field to OptimizerParamsHandler (#502)
• Improved ProgressBar with TerminateOnNan (#506)
• Support for layer freezing with Tensorboard integration (#515)
• Improved OutputHandler API (#531)
• Improved create_lr_scheduler_with_warmup (#556)
• Added "all" option to metric_names in contrib loggers (#565)
• Added GPU usage info as metric (#569)
• Other bug fixes

Notebook examples

• Added Cycle-GAN notebook (#500)
• Finetune EfficientNet-B0 on CIFAR100 (#544)
• Added Fashion MNIST jupyter notebook (#549)

Updated nighlty builds

From pip:

pip install --pre pytorch-ignite

From conda (this suggests to install pytorch nightly release instead of stable version as dependency):

conda install ignite -c pytorch-nightly

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Acknowledgments

🎉 Thanks to our community and all our contributors for the issues, PRs and 🌟 ⭐️ 🌟 !
💯 We really appreciate your implication into the project (in alphabetical order):

@ANUBHAVNATANI, @Bibonaut, @Evpok, @Hiroshiba, @JeroenDelcour, @Mxbonn, @anmolsjoshi, @asford, @bosr, @johnstill, @marrrcin, @vfdev-5, @willfrey