28c19ab58d0de8e2739656b8fad3db2b0cce54cf
5 Commits
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8abe4930d3 |
[Time-Series] informer model (#21099)
* added informer to gitignore * added informer to gitignore * WIP informer2020 * added checking that instantiate works * added config using gluonTS by kashif * WIP config * adding informeConfig. need to remove FeatureEmbedder * done InformerConfig, but need to change the names * Done informer model init. working on enc-dec * added things to address, after reading again enc-dec in the paper * done modeling - checking initialization work * added informer to gitignore * WIP informer2020 * added checking that instantiate works * added config using gluonTS by kashif * WIP config * adding informeConfig. need to remove FeatureEmbedder * done InformerConfig, but need to change the names * Done informer model init. working on enc-dec * added things to address, after reading again enc-dec in the paper * done modeling - checking initialization work * moved enc-dec init to InformerEncoder/Decoder init * added 'init_std' to config, now model init works! * WIP conversion script, and added code sources * WIP conversion script: loading original informer pth works * WIP conversion script: change defaults in the config * WIP conversion script: supporting Informer input embedding * WIP conversion script: added parameters for the informer embed * WIP conversion script: change dim_feedforward=2048 * WIP conversion script: remove unused args for loading checkpoint * just cleaning up * DataEmbedding removed, after thinking with Kashif * working on forward pass * WIP forward pass: trying to establish working batch for forward pass * cleaning and finalizing * adding HF names and docs * init after cleaning works * WIP in tests * added docs for the informer specific args * fix style * undo change * cleaning informer, now need to work only enc-dec * initial enc-dec classes * added encoder and decoder * added todo * add todos for conv_layers * added decoder docs from vanilla * added encoder docs from vanilla * remove encoder decoder from the original informer * removed AttentionLayer from the original paper * removed TriangularCausalMask, same as decoder_attention_mask * initial sparse attention * use conv_layers * fixed test_config test * fix parenthesis when itearting zip(layers, conv_layers) * error found in prob attention, added sizes as comments * fix sizes * added proposal for q_reduce indexing, and remove unused * WIP ProbMask, and changed factor=2 for testing * remove unused libs for this PR for creating the env * fix checking the attn_weights.size() after bmm * Q_reduce: changed from torch.gather to simple slicing * WIP calculate final attn_output * finish adding v_aggregated, attn_output ready * changed tgt_len to u in attention_mask, need to fix the size error * comment attention_mask for encoder, and fix if cond for v_agg * added ProbMask support (wip), removed old original code * finished ProbMask 😃 * Revert "remove unused libs for this PR for creating the env" This reverts commit 11a081e09e92771e51a5d2758d53a9afb59547f0. * fixes * make style * fix initial tests * fix more tests * dry * make style * remove unused files * style * added integration tests * fix num_static_real_features * fix header * remove unused function * fix example * fix docs * Update src/transformers/models/informer/configuration_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/informer/modeling_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/informer/configuration_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/informer/configuration_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/informer/configuration_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/informer/configuration_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fixes for reviewer * use prediction_length from model * fix style * fixed informer.mdx * added to index * updated readme * undo * make fix-copies * typo * fix copy * added Informer to toctree * in order * fixed comments * remove unneeded new lines in docs * make static real and cat optional * fix use of distil conv layers * fixed integration test * added checkpoint for convlayer * make fix-copies * updated from time series model * make fix-copies * copy decoder * fix unit tests * updated scaling config * fix integration tests * IGNORE_NON_TESTED * IGNORE_NON_AUTO_CONFIGURED * IGNORE_NON_AUTO_CONFIGURED * updated check configs * fix formatting * undo change from time series * prediction_length should not be None * aliign with the blog: prettify ProbSparse and change attention_factor to sampling_factor * make style * make fix-copies * niels CR: update contributed by * niels CR: update configuration_informer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * niels CR: update kashif -> huggingface Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * niels CR: `sampling_factor` only relevant when `attention_type`=prob * make style * fixed U_part: added multiplication by `L_Q` * fixed bug: remove `is not None` from `if config.distil` * fixed test: `decoder_seq_length` to `encoder_seq_length` in cross_attentions check * fix integration tests * updated model hub * do not shift as in training * undo * fix make-copies * make fix-copies * added `if prediction_length is None` * changed `ProbSparseAttention` to `InformerProbSparseAttention` * changed `V_sum` -> `v_mean_dim_time` * changed `ConvLayer` to `InformerConvLayer` and fixed `super()` * TimeSeriesTansformer->Informer in decoder's Copied from * more descriptive in ProbSparse * make style * fix coped from * Revert "added `if prediction_length is None`" This reverts commit b4cbddfa05e3bd739b79569cd3c3b89e316f2451. * fixed indent * use InformerSinusoidalPositionalEmbedding * make fix-style * fix from #21860 * fix name * make fix-copies * use time series utils * fix dec num_heads * docstring * added time series util doc * _import_structure * formatting * changes from review * make style * fix docs * fix doc * removed NegativeLogLikelihood --------- Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> |
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e4bacf6614 |
[WIP] add SpeechT5 model (#18922)
* make SpeechT5 model by copying Wav2Vec2 * add paper to docs * whoops added docs in wrong file * remove SpeechT5Tokenizer + put CTC back in the name * remove deprecated class * remove unused docstring * delete SpeechT5FeatureExtractor, use Wav2Vec2FeatureExtractor instead * remove classes we don't need right now * initial stab at speech encoder prenet * add more speech encoder prenet stuff * improve SpeechEncoderPrenet * add encoder (not finished yet) * add relative position bias to self-attention * add encoder CTC layers * fix formatting * add decoder from BART, doesn't work yet * make it work with generate loop * wrap the encoder into a speech encoder class * wrap the decoder in a text decoder class * changed my mind * changed my mind again ;-) * load decoder weights, make it work * add weights for text decoder postnet * add SpeechT5ForCTC model that uses only the encoder * clean up EncoderLayer and DecoderLayer * implement _init_weights in SpeechT5PreTrainedModel * cleanup config + Encoder and Decoder * add head + cross attention masks * improve doc comments * fixup * more cleanup * more fixup * TextDecoderPrenet works now, thanks Kendall * add CTC loss * add placeholders for other pre/postnets * add type annotation * fix freeze_feature_encoder * set padding tokens to 0 in decoder attention mask * encoder attention mask downsampling * remove features_pen calculation * disable the padding tokens thing again * fixup * more fixup * code review fixes * rename encoder/decoder wrapper classes * allow checkpoints to be loaded into SpeechT5Model * put encoder into wrapper for CTC model * clean up conversion script * add encoder for TTS model * add speech decoder prenet * add speech decoder post-net * attempt to reconstruct the generation loop * add speech generation loop * clean up generate_speech * small tweaks * fix forward pass * enable always dropout on speech decoder prenet * sort declaration * rename models * fixup * fix copies * more fixup * make consistency checker happy * add Seq2SeqSpectrogramOutput class * doc comments * quick note about loss and labels * add HiFi-GAN implementation (from Speech2Speech PR) * rename file * add vocoder to TTS model * improve vocoder * working on tokenizer * more better tokenizer * add CTC tokenizer * fix decode and batch_code in CTC tokenizer * fix processor * two processors and feature extractors * use SpeechT5WaveformFeatureExtractor instead of Wav2Vec2 * cleanup * more cleanup * even more fixup * notebooks * fix log-mel spectrograms * support reduction factor * fixup * shift spectrograms to right to create decoder inputs * return correct labels * add labels for stop token prediction * fix doc comments * fixup * remove SpeechT5ForPreTraining * more fixup * update copyright headers * add usage examples * add SpeechT5ProcessorForCTC * fixup * push unofficial checkpoints to hub * initial version of tokenizer unit tests * add slow test * fix failing tests * tests for CTC tokenizer * finish CTC tokenizer tests * processor tests * initial test for feature extractors * tests for spectrogram feature extractor * fixup * more fixup * add decorators * require speech for tests * modeling tests * more tests for ASR model * fix imports * add fake tests for the other models * fixup * remove jupyter notebooks * add missing SpeechT5Model tests * add missing tests for SpeechT5ForCTC * add missing tests for SpeechT5ForTextToSpeech * sort tests by name * fix Hi-Fi GAN tests * fixup * add speech-to-speech model * refactor duplicate speech generation code * add processor for SpeechToSpeech model * add usage example * add tests for speech-to-speech model * fixup * enable gradient checkpointing for SpeechT5FeatureEncoder * code review * push_to_hub now takes repo_id * improve doc comments for HiFi-GAN config * add missing test * add integration tests * make number of layers in speech decoder prenet configurable * rename variable * rename variables * add auto classes for TTS and S2S * REMOVE CTC!!! * S2S processor does not support save/load_pretrained * fixup * these models are now in an auto mapping * fix doc links * rename HiFiGAN to HifiGan, remove separate config file * REMOVE auto classes * there can be only one * fixup * replace assert * reformat * feature extractor can process input and target at same time * update checkpoint names * fix commit hash |
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f719c0377f | Minor typo in prose of model outputs documentation. (#18848) | ||
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5a9957358c |
Add Wav2Vec2Conformer (#16812)
* save intermediate * add wav2vec2 conformer * add more code * more * first test passes * make all checkpoints work * update * up * more clean ups * save clean-up * save clean-up * save more * remove bogus * finalize design conformer * remove vision * finish all tests * more changes * finish code * add doc tests * add slow tests * fix autoconfig test * up * correct docstring * up * update * fix * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com> * Update docs/source/en/model_doc/wav2vec2-conformer.mdx * upload * save copied from * correct configs * fix model outputs * add to docs * fix imports * finish * finish code * correct copied from * correct again * correct make fix * improve make fix copies * save * correct fix copy from * correct init structure * correct * fix import * apply suggestions Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com> |
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b9a768b3ff |
Enable doc in Spanish (#16518)
* Reorganize doc for multilingual support * Fix style * Style * Toc trees * Adapt templates |