Core
Various improvements in the core part of the library:
-
Add
epoch_boundparameter toRunningAverage(#488) -
Bug fixes with Confusion matrix, new implementation (#572) - BC breaking
-
Added
event_to_attrin register_events (#523) -
Added accumulative single variable metrics (#524)
-
should_terminateis reset between runs (#525) -
to_onehotreturns 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
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