Add Pop2Piano (#21785)

* init commit

* config updated also some modeling

* Processor and Model config combined

* extraction pipeline(upto before spectogram & mel_conditioner) added but not properly tested

* model loading successful!

* feature extractor done!

* FE can now be called from HF

* postprocessing added in fe file

* same as prev commit

* Pop2PianoConfig doc done

* cfg docs slightly changed

* fe docs done

* batched

* batched working!

* temp

* v1

* checking

* trying to go with generate

* with generate and model tests passed

* before rebasing

* .

* tests done docs done remaining others & nits

* nits

* LogMelSpectogram shifted to FeatureExtractor

* is_tf rmeoved from pop2piano/init

* import solved

* tokenization tests added

* minor fixed regarding modeling_pop2piano

* tokenizer changed to only return midi_object and other changes

* Updated paper abstract(Camera-ready version) (#2)

* more comments and nits

* ruff changes

* code quality fix

* sg comments

* t5 change added and rebased

* comments except batching

* batching done

* comments

* small doc fix

* example removed from modeling

* ckpt

* forward it compatible with fe and generation done

* comments

* comments

* code-quality fix(maybe)

* ckpts changed

* doc file changed from mdx to md

* test fixes

* tokenizer test fix

* changes

* nits done main changes remaining

* code modified

* Pop2PianoProcessor added with tests

* other comments

* added Pop2PianoProcessor to dummy_objects

* added require_onnx to modeling file

* changes

* update .md file

* remove extra line in index.md

* back to the main index

* added pop2piano to index

* Added tokenizer.__call__ with valid args and batch_decode and aligned the processor part too

* changes

* added return types to 2 tokenizer methods

* the PR build test might work now

* added backends

* PR build fix

* vocab added

* comments

* refactored vocab into 1 file

* added conversion script

* comments

* essentia version changed in .md

* comments

* more tokenizer tests added

* minor fix

* tests extended for outputs acc check

* small fix

---------

Co-authored-by: Jongho Choi <sweetcocoa@snu.ac.kr>
This commit is contained in:
Susnato Dhar
2023-08-21 21:05:00 +05:30
committed by GitHub
parent 6f041fcbb8
commit 450a181d8b
38 changed files with 5284 additions and 0 deletions

View File

@@ -360,6 +360,7 @@ Flax, PyTorch, TensorFlow 설치 페이지에서 이들을 conda로 설치하는
1. **[Pix2Struct](https://huggingface.co/docs/transformers/model_doc/pix2struct)** (Google 에서 제공)은 Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova.의 [Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding](https://arxiv.org/abs/2210.03347)논문과 함께 발표했습니다.
1. **[PLBart](https://huggingface.co/docs/transformers/model_doc/plbart)** (UCLA NLP 에서) Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang 의 [Unified Pre-training for Program Understanding and Generation](https://arxiv.org/abs/2103.06333) 논문과 함께 발표했습니다.
1. **[PoolFormer](https://huggingface.co/docs/transformers/model_doc/poolformer)** (Sea AI Labs 에서) Yu, Weihao and Luo, Mi and Zhou, Pan and Si, Chenyang and Zhou, Yichen and Wang, Xinchao and Feng, Jiashi and Yan, Shuicheng 의 [MetaFormer is Actually What You Need for Vision](https://arxiv.org/abs/2111.11418) 논문과 함께 발표했습니다.
1. **[Pop2Piano](https://huggingface.co/docs/transformers/main/model_doc/pop2piano)** released with the paper [Pop2Piano : Pop Audio-based Piano Cover Generation](https://arxiv.org/abs/2211.00895) by Jongho Choi, Kyogu Lee.
1. **[ProphetNet](https://huggingface.co/docs/transformers/model_doc/prophetnet)** (Microsoft Research 에서) Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou 의 [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://arxiv.org/abs/2001.04063) 논문과 함께 발표했습니다.
1. **[PVT](https://huggingface.co/docs/transformers/model_doc/pvt)** (Nanjing University, The University of Hong Kong etc. 에서 제공)은 Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao.의 [Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions](https://arxiv.org/pdf/2102.12122.pdf)논문과 함께 발표했습니다.
1. **[QDQBert](https://huggingface.co/docs/transformers/model_doc/qdqbert)** (NVIDIA 에서) Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev and Paulius Micikevicius 의 [Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation](https://arxiv.org/abs/2004.09602) 논문과 함께 발표했습니다.