PyText v0.3.2

New features

• Add Roberta model into BertPairwiseModel (#1336)
• Support read file from http URL (#1317)
• add a new PyText get_num_examples_from_batch function in model (#1319)
• Add support for length label smoothing (#1308)
• Add new metrics type for Masked Seq2Seq Joint Model (#1304)
• Add mask generator and strategy (#1302)
• Add separate logging for label loss and length loss (#1294)
• Add tensorizer support for masking of target tokens (#1297)
• Add length prediction and basic masked generator (#1290)
• Add self attention option to conv_encoder and conv_decoder (#1291)
• Entity Saliency modeling on PyText: EntitySalienceMetricReporter/EntitySalienceTask
• In-batch negative training for BertPairwiseModel
• Support embedding from decoder (#1284)
• Add dense features to Roberta
• Add projection layer to HuggingFace encoder (#1273)
• add PyText Embedding TorchScript Wrapper
• Add option to pad missing label in LabelListTensorizer (#1269)
• Integrate PET and Introduce ElasticTrainer (#1266)
• support PoolingType in DocNN. (#1259)
• Added WordSeqEmbedding (#1255)
• Open source Assistant NLU seq2seq model (#1236)
• Support multi label classification
• BART in decoupled model

Bug fixes

• Fix Incorrect State Dict Assumption (#1326)
• Bug fix for "RoBERTaTensorizer object has no attribute is_input" (#1334)
• Cast model output to cpu (#1329)
• Fix OSS predict-py API (#1320)
• Fix "calling median on empty tensor" issue in MR (#1322)
• Add ScriptDoNothingTokenizer so that torchscriptification of SPM does not fail (#1316)
• Fix creating generator everytime (#1301)
• fix dense feature for fp16
• Avoid edge cases with quantization by setting a known seed (#1295)
• Make torchscript predictions even on empty text / token inputs
• fix dense feature TorchScript typing (#1281)
• avoid zero division error in metrics reporter (#1271)
• Fix contiguous issue in bilstm export (#1270)
• fix debug file generation for multilabel classification (#1247)
• Fix fp16 optimizer attribute name

Other

• Simplify contextual embedding dimension computation in PyText (#1331)
• New Debug File for masked seq2seq
• Move MockConfigLoader to OSS (#1324)
• Pass in optimizer config instead of create_optimizer to trainer
• Remove unnecessary torch.no_grad() block (#1323)
• Fix Memory Issues in Metric Reporter for Classification Tasks over large Label Spaces
• Add contextual embedding support to OS seq2seq model (#1299)
• recover xlm_r tutorial notebook (#1305)
• Enable controlling bias in MLP decoder
• Migrate serving tutorial to TorchScript (#1310)
• delete caffe2 export (#1307)
• add whitelist for ONNX export
• Use dynamic quantization api for BeamSearch (#1303)
• Remove requirement that eos/bos be supplied for sequence export. (#1300)
• Multicolumn support
• Multicolumn support in torchscriptify
• Add caching support to RawExample and batch predict API (#1298)
• Add save-pytext-snapshot command to PyText cmdline (#1285)
• Update with Whatsapp calling data + support dictionary features (#1293)
• add arrange_caffe2_model_inputs in BaseModel (#1292)
• Replace unit-tests on LMModel and FLLanguageModelingTask by LiteLMModel and FLLiteLMTask (#1296)
• changes to make mbart work (#1911)
• handle encoder and decoder embedding
• Add tutorial for semantic parsing. (#1288)
• Add new fb beam search with fused operator (#1287)
• Move generator builder to constructor so that it can easily overridden. (#1286)
• Torchscriptify ELTensorizer (#1282)
• Torchscript export for Seq2Seq model (#1265)
• Change Seq2Seq model from_config() to a more general api (#1280)
• add max_seq_len to DocNN TorchScript model (#1279)
• support XLM-R model Embedding in TorchScript (#1278)
• Generic PyText Checkpoint Manager Interface (#1267)
• Fix backward compatibility issue of pad_missing in LabelListTensorizer (#1277)
• Update mean reduction in NLLLoss (#1272)
• migrate pages.integrity.scam.docnn_models.xxx (#1275)
• Unify model input for ByteTokensDocumentModel (#1274)
• Torchscriptify TokenTensorizer
• Allow dictionaries to overwrite entries with #fairseq:overwrite comment (#1073)
• Make WordSeqEmbedding ONNX compatible
• If the snapshot path provided is not valid, throw error (#1268)
• support vocab filter by min count
• Unify input for TorchScript Tensorizers and Models (#1256)
• Torchscriptify XLM-R
• Add class logging to task (#1264)
• Add usage logging to exporter (#1262)
• Add usage logging across models (#1263)
• Usage logging on data classes (#1261)
• GPT2 BPE add lower casing support (#1260)
• FAISS Embedding Search Space [3/5]
• Return len of tokens of each sequence in SeqTokenTensorizer (#1254)
• Vocab Limited Pretrained Embedding [2/5] (#1248)
• add Stage.OTHERS and allow TB to print to a seperate prefix not in (TRAIN, TEST, EVAL) (#1258)
• Add option to skip 2 stage tokenizer and bpe decode sequences in the debug file (#1257)
• Add Testcase for Wordpiece Tokenizer (#1249)
• modify accuracy calculation for multi-label classification (#1244)
• Enable tests in pytext/config:pytext_all_config_test
• Introduce Class Usage Logging (#1243)
• Make PyText compatible with Any type (#1242)
• Make dict_embedding Torchscript friendly (#1240)
• Support MultipleData for export and kd generation
• delete flaky/broken tests (#1238)
• Add support for returning start & end indices.