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Add Audio Spectogram Transformer (#19981)

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* First draft

* Make conversion script work

* Add id2label mapping, run code quality

* Fix copies

* Add first draft of feature extractor

* Update conversion script to use feature extractor

* Make more tests pass

* Add docs

* update input_features to input_values + pad by default to max length

* Fix doc tests

* Add feature extractor tests

* Add proper padding/truncation to feature extractor

* Add support for conversion of all audioset checkpoints

* Improve docs and extend conversion script

* Fix README

* Rename spectogram to spectrogram

* Fix copies

* Add integration test

* Remove dummy conv

* Update to ast

* Update organization

* Fix init

* Rename model to AST

* Add require_torchaudio annotator

* Move import of ASTFeatureExtractor under a is_speech_available

* Fix rebase

* Add pipeline config

* Update name of classifier head

* Rename time_dimension and frequency_dimension for clarity

* Remove print statement

* Fix pipeline test

* Fix pipeline test

* Fix index table

* Fix init

* Fix conversion script

* Rename to ForAudioClassification

* Fix index table

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
This commit is contained in:
NielsRogge
2022-11-21 18:58:54 +01:00
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parent 1e3f17b5ab
commit 4973d2a04c
28 changed files with 2014 additions and 147 deletions
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README_es.md
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@@ -262,6 +262,7 @@ Número actual de puntos de control: ![](https://img.shields.io/endpoint?url=htt
🤗 Transformers actualmente proporciona las siguientes arquitecturas (ver [aquí](https://huggingface.co/docs/transformers/model_summary) para un resumen de alto nivel de cada uno de ellas.):
1. **[ALBERT](https://huggingface.co/docs/transformers/model_doc/albert)** (from Google Research and the Toyota Technological Institute at Chicago) released with the paper [ALBERT: A Lite BERT for Self-supervised Learning of Language Representations](https://arxiv.org/abs/1909.11942), by Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut.
1. **[Audio Spectrogram Transformer](https://huggingface.co/docs/transformers/main/model_doc/audio-spectrogram-transformer)** (from MIT) released with the paper [AST: Audio Spectrogram Transformer](https://arxiv.org/abs/2104.01778) by Yuan Gong, Yu-An Chung, James Glass.
1. **[BART](https://huggingface.co/docs/transformers/model_doc/bart)** (from Facebook) released with the paper [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://arxiv.org/abs/1910.13461) by Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov and Luke Zettlemoyer.
1. **[BARThez](https://huggingface.co/docs/transformers/model_doc/barthez)** (from École polytechnique) released with the paper [BARThez: a Skilled Pretrained French Sequence-to-Sequence Model](https://arxiv.org/abs/2010.12321) by Moussa Kamal Eddine, Antoine J.-P. Tixier, Michalis Vazirgiannis.
1. **[BARTpho](https://huggingface.co/docs/transformers/model_doc/bartpho)** (from VinAI Research) released with the paper [BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese](https://arxiv.org/abs/2109.09701) by Nguyen Luong Tran, Duong Minh Le and Dat Quoc Nguyen.