Summary of changes:
PRs:
- A lot of code cleanup thanks a ton to @lgeiger ! This goes a long way with regards to code maintainability and is much appreciated. Ex: PR #1361 , #1350 , #1344 , #1346 , #1345 , #1324
- Fixing LM decode, thanks @mikeymezher - PR #1282
- More fast decoding by @gcampax, thanks! - PR #999
- Avoid error on beam search - PR #1302 by @aeloyq , thanks!
- Fix invalid list comprehension, unicode simplifications, py3 fixes #1343, #1318 , #1321, #1258 thanks @cclauss !
- Fix is_generate_per_split hard to spot bug, thanks a lot to @kngxscn in PR #1322
- Fix py3 compatibility issues in PR #1300 by @ywkim , thanks a lot again!
- Separate train and test data in MRPC and fix broken link in PR #1281 and #1247 by @ywkim - thanks for the hawk eyed change!
- Fix universal transformer decoding by @artitw in PR #1257
- Fix babi generator by @artitw in PR #1235
- Fix transformer moe in #1233 by @twilightdema - thanks!
- Universal Transformer bugs corrected in #1213 by @cfiken - thanks!
- Change beam decoder stopping condition, makes decode faster in #965 by @mirkobronzi - many thanks!
- Bug fix, problem_0_steps variable by @senarvi in #1273
- Fixing a typo, by @hsm207 in PR #1329 , thanks a lot!
New Model and Problems:
- New problem and model by @artitw in PR #1290 - thanks!
- New model for scalar regression in PR #1332 thanks to @Kotober
- Text CNN for classification in PR #1271 by @ybbaigo - thanks a lot!
- en-ro translation by @lukaszkaiser !
- CoNLL2002 Named Entity Recognition problem added in #1253 by @ybbaigo - thanks!
New Metrics:
- Pearson Correlation metrics in #1274 by @luffy06 - thanks a lot!
- Custom evaluation metrics, this was one of the most asked features, thanks a lot @ywkim in PR #1336
- Word Error Rate metric by @stefan-falk in PR #1242 , many thanks!
- SARI score for paraphrasing added.
Enhancements:
- Fast decoding !! Huge thanks to @aeloyq in #1295
- Fast GELU unit
- Relative dot product visualization PR #1303 thanks @aeloyq !
- New MTF models and enhacements, thanks to Noam, Niki and the MTF team
- Custom eval hooks in PR #1284 by @theorm - thanks a lot !
RL:
Lots of commits to Model Based Reinforcement Learning code by @konradczechowski @koz4k @blazejosinski @piotrmilos - thanks all !