PyText v0.2.2

Note: this is the last release with _Deprecated classes. Those classes will be removed in the next release.

New Features:

• DeepCNN Representation for word tagging
• Combine KLDivergenceBCELoss with SoftHardBCELoss and F.cross_entropy() in CrossEntropyLoss (#689)
• add dense feature support for doc model (#710)
• add torchscript quantizaiton support in pytext
• pytext multi-label support (#731)
• open source transformer representations (#736)
• open source transformer based models - data, tensorizers and tokenizer (#708)
• Create AlternatingRandomizedBatchSampler (#737)
• open source MaskedLM and BERT models (#734)
• Support bytes input in word tagging model OSS (#745)
• open source extractive question answering models (#742)
• torchscriptify for ensemle task
• enabled lmlstm labels exporting (#767)
• Enable dense features in ByteTokensDocumentModel (#763)
• created bilstm dropout condition (#769)
• enabled lmlstm caffe2 exporting (#766)
• PolynomialDecayScheduler (#791)
• removed bilstm dependence on seq_lengths (#776)
• fp16 optimizer (#782)
• Add Dense Feature Normalization to FloatListTensorizer and DocModel (#859)
• Add Sparsifier component to PyText and L0-projection based sparsifier (#860)
• implemented cnn pooling for doc classification (#872)
• implemented bottleneck separable convolutions (#855)
• Add eps to Adam (#858)
• implemented mobile exporter (#785)
• support starting training from saved checkpoint (#824)
• implemented separable convolutions (#830)
• implemented gelu activations (#829)
• implemented causal convolutions (#811)
• implemented dilation for convolutions (#810)
• created weight norm option (#809)
• Ordered Neuron LSTM (#854)
• Add PersonalizedByteDocModel (#816)
• CNN based language models (#827)
• improve csv support in TSVDataSource (#777)
• Change default batch sampler DisjointMultitaskData to RoundRobinBatchSampler (#802)
• Support using serialized pretrained embedding file (#797)

Documentation / Usability / Logging:

• Fewer out-of-vocab print messages, with some stats (#697)
• Echo epoch number to console while training (#712)
• Separate timing for prediction and metric calculation. (#738)
• multi-label soft metrics (#754)
• changed lm metric reporting (#765)
• fix data source tutorial (#762)
• fix doc sphinx deprecation warning (#775)
• Add the ability to pass parameter values to gen-default-config (#856)
• Remove "pytext/" from paths in demo json config (#878)
• New documentation about hacking pytext and dealing with github. (#862)
• install_deps supports updates (#863)
• Reduce number of PEP print (#861)
• better error message for config with unknown component (#801)
• Add Recall at Precision Thresholds to Config (#792)
• implemented perplexity reductions for lm score reporting (#799)
• adapt prediction workflow to new design (#746)

Bug fixes:

• block sharded tsv eval/test fix (#698)
• Fix BoundaryPooling tracing (#713)
• fixes LMLSTM weight tying bug (#704)
• Fix duplicate entries in vocab (#721)
• Bugfix for trainer not reporting eval results (#740)
• Reintroduce metrics export in new task (#748)
• fix open source tests (#750)
• Fix missing init_tensorizers arg (#893)
• Fix intent slot metric reporter not working with byte offset (#883)
• Fix issue with some tensorizers still re-initializing vocab when loaded from saved state (#848)
• fixed overflow error in lm reporting (#831)
• fix BlockShardedTSVDataSource (#832)

v0.2.1
(skipped because of packaging issues)