**Notes on versioning** ## [Unreleased] ### Fixes and improvements ## [0.9.1](https://github.com/OpenNMT/OpenNMT-py/tree/0.9.1) (2019-06-13) * New mechanism for MultiGPU training "1 batch producer / multi batch consumers" resulting in big memory saving when handling huge datasets * New APEX AMP (mixed precision) API * Option to overwrite shards when preprocessing * Small fixes and add-ons ## [0.9.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.9.0) (2019-05-16) * Faster vocab building when processing shards (no reloading) * New dataweighting feature * New dropout scheduler. * Small fixes and add-ons ## [0.8.2](https://github.com/OpenNMT/OpenNMT-py/tree/0.8.2) (2019-02-16) * Update documentation and Library example * Revamp args * Bug fixes, save moving average in FP32 * Allow FP32 inference for FP16 models ## [0.8.1](https://github.com/OpenNMT/OpenNMT-py/tree/0.8.1) (2019-02-12) * Update documentation * Random sampling scores fixes * Bug fixes ## [0.8.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.8.0) (2019-02-09) * Many fixes and code cleaning thanks @flauted, @guillaumekln * Datasets code refactor (thanks @flauted) you need to r-preeprocess datasets ### New features * FP16 Support: Experimental, using Apex, Checkpoints may break in future version. * Continuous exponential moving average (thanks @francoishernandez, and Marian) * Relative positions encoding (thanks @francoishernanndez, and Google T2T) * Deprecate the old beam search, fast batched beam search supports all options ## [0.7.2](https://github.com/OpenNMT/OpenNMT-py/tree/0.7.2) (2019-01-31) * Many fixes and code cleaning thanks @bpopeters, @flauted, @guillaumekln ### New features * Multilevel fields for better handling of text featuer embeddinggs. ## [0.7.1](https://github.com/OpenNMT/OpenNMT-py/tree/0.7.1) (2019-01-24) * Many fixes and code refactoring thanks @bpopeters, @flauted, @guillaumekln ### New features * Random sampling thanks @daphnei * Enable sharding for huge files at translation ## [0.7.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.7.0) (2019-01-02) * Many fixes and code refactoring thanks @benopeters * Migrated to Pytorch 1.0 ## [0.6.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.6.0) (2018-11-28) * Many fixes and code improvements * New: Ability to load a yml config file. See examples in config folder. ## [0.5.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.5.0) (2018-10-24) * Fixed advance n_best beam in translate_batch_fast * Fixed remove valid set vocab from total vocab * New: Ability to reset optimizer when using train_from * New: create_vocabulary tool + fix when loading existing vocab. ## [0.4.1](https://github.com/OpenNMT/OpenNMT-py/tree/0.4.1) (2018-10-11) * Fixed preprocessing files names, cleaning intermediary files. ## [0.4.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.4.0) (2018-10-08) * Fixed Speech2Text training (thanks Yuntian) * Removed -max_shard_size, replaced by -shard_size = number of examples in a shard. Default value = 1M which works fine in most Text dataset cases. (will avoid Ram OOM in most cases) ## [0.3.0](https://github.com/OpenNMT/OpenNMT-py/tree/0.3.0) (2018-09-27) * Now requires Pytorch 0.4.1 * Multi-node Multi-GPU with Torch Distributed New options are: -master_ip: ip address of the master node -master_port: port number of th emaster node -world_size = total number of processes to be run (total GPUs accross all nodes) -gpu_ranks = list of indices of processes accross all nodes * gpuid is deprecated See examples in https://github.com/OpenNMT/OpenNMT-py/blob/master/docs/source/FAQ.md * Fixes to img2text now working * New sharding based on number of examples * Fixes to avoid 0.4.1 deprecated functions. ## [0.2.1](https://github.com/OpenNMT/OpenNMT-py/tree/0.2.1) (2018-08-31) ### Fixes and improvements * First compatibility steps with Pytorch 0.4.1 (non breaking) * Fix TranslationServer (when various request try to load the same model at the same time) * Fix StopIteration error (python 3.7) ### New features * Ensemble at inference (thanks @Waino) ## [0.2](https://github.com/OpenNMT/OpenNMT-py/tree/v0.2) (2018-08-28) ### improvements * Compatibility fixes with Pytorch 0.4 / Torchtext 0.3 * Multi-GPU based on Torch Distributed * Average Attention Network (AAN) for the Transformer (thanks @francoishernandez ) * New fast beam search (see -fast in translate.py) (thanks @guillaumekln) * Sparse attention / sparsemax (thanks to @bpopeters) * Refactoring of many parts of the code base: - change from -epoch to -train_steps -valid_steps (see opts.py) - reorg of the logic train => train_multi / train_single => trainer * Many fixes / improvements in the translationserver (thanks @pltrdy @francoishernandez) * fix BPTT ## [0.1](https://github.com/OpenNMT/OpenNMT-py/tree/v0.1) (2018-06-08) ### First and Last Release using Pytorch 0.3.x