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Add BROS (#23190)

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* add Bros boilerplate

* copy and pasted modeling_bros.py from official Bros repo

* update copyright of bros files

* copy tokenization_bros.py from official repo and update import path

* copy tokenization_bros_fast.py from official repo and update import path

* copy configuration_bros.py from official repo and update import path

* remove trailing period in copyright line

* copy and paste bros/__init__.py from official repo

* save formatting

* remove unused unnecessary pe_type argument - using only crel type

* resolve import issue

* remove unused model classes

* remove unnecessary tests

* remove unused classes

* fix original code's bug - layer_module's argument order

* clean up modeling auto

* add bbox to prepare_config_and_inputs

* set temporary value to hidden_size (32 is too low because of the of the
Bros' positional embedding)

* remove decoder test, update create_and_check* input arguemnts

* add missing variable to model tests

* do make fixup

* update bros.mdx

* add boilerate plate for no_head inference test

* update BROS_PRETRAINED_MODEL_ARCHIVE_LIST (add naver-clova-ocr prefix)

* add prepare_bros_batch_inputs function

* update modeling_common to add bbox inputs in Bros Model Test

* remove unnecessary model inference

* add test case

* add model_doc

* add test case for token_classification

* apply fixup

* update modeling code

* update BrosForTokenClassification loss calculation logic

* revert logits preprocessing logic to make sure logits have original shape

* - update class name

* - add BrosSpadeOutput
- update BrosConfig arguments

* add boilerate plate for no_head inference test

* add prepare_bros_batch_inputs function

* add test case

* add test case for token_classification

* update modeling code

* update BrosForTokenClassification loss calculation logic

* revert logits preprocessing logic to make sure logits have original shape

* apply masking on the fly

* add BrosSpadeForTokenLinking

* update class name
put docstring to the beginning of the file

* separate the logits calculation logic and loss calculation logic

* update logic for loss calculation so that logits shape doesn't change
when return

* update typo

* update prepare_config_and_inputs

* update dummy node initialization

* update last_hidden_states getting logic to consider when return_dict is False

* update box first token mask param

* bugfix: remove random attention mask generation

* update keys to ignore on load missing

* run make style and quality

* apply make style and quality of other codes

* update box_first_token_mask to bool type

* update index.md

* apply make style and quality

* apply make fix-copies

* pass check_repo

* update bros model doc

* docstring bugfix fix

* add checkpoint for doc, tokenizer for doc

* Update README.md

* Update docs/source/en/model_doc/bros.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update bros.md

* Update src/transformers/__init__.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/bros.md

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Apply suggestions from code review

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* apply suggestions from code review

* apply suggestions from code review

* revert test_processor_markuplm.py

* Update test_processor_markuplm.py

* apply suggestions from code review

* apply suggestions from code review

* apply suggestions from code review

* update BrosSpadeELForTokenClassification head name to entity linker

* add doc string for config params

* update class, var names to more explicit and apply suggestions from code review

* remove unnecessary keys to ignore

* update relation extractor to be initialized with config

* add bros processor

* apply make style and quality

* update bros.md

* remove bros tokenizer, add bros processor that wraps bert tokenizer

* revert change

* apply make fix-copies

* update processor code, update itc -> initial token, stc -> subsequent token

* add type hint

* remove unnecessary condition branches in embedding forward

* fix auto tokenizer fail

* update docstring for each classes

* update bbox input dimension as standard 2 points and convert them to 4
points in forward pass

* update bros docs

* apply suggestions from code review : update Bros -> BROS in bros.md

* 1. box prefix var -> bbox
2. update variable names to be more explicit

* replace einsum with torch matmul

* apply style and quality

* remove unused argument

* remove unused arguments

* update docstrings

* apply suggestions from code review: add BrosBboxEmbeddings, replace
einsum with classical matrix operations

* revert einsum update

* update bros processor

* apply suggestions from code review

* add conversion script for bros

* Apply suggestions from code review

* fix readme

* apply fix-copies

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
This commit is contained in:
Jinho Park
2023-09-15 02:02:37 +09:00
committed by GitHub
parent 95fe0f5d80
commit 17fdd35481
28 changed files with 2453 additions and 8 deletions
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docs/source/ms/index.md
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@@ -76,6 +76,7 @@ Dokumentasi disusun kepada lima bahagian:
1. **[BLOOM](model_doc/bloom)** (from BigScience workshop) released by the [BigScience Workshop](https://bigscience.huggingface.co/).
1. **[BORT](model_doc/bort)** (from Alexa) released with the paper [Optimal Subarchitecture Extraction For BERT](https://arxiv.org/abs/2010.10499) by Adrian de Wynter and Daniel J. Perry.
1. **[BridgeTower](model_doc/bridgetower)** (from Harbin Institute of Technology/Microsoft Research Asia/Intel Labs) released with the paper [BridgeTower: Building Bridges Between Encoders in Vision-Language Representation Learning](https://arxiv.org/abs/2206.08657) by Xiao Xu, Chenfei Wu, Shachar Rosenman, Vasudev Lal, Wanxiang Che, Nan Duan.
1. **[Bros](model_doc/bros)** (from NAVER) released with the paper [BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents](https://arxiv.org/abs/2108.04539) by Teakgyu Hong, Donghyun Kim, Mingi Ji, Wonseok Hwang, Daehyun Nam, Sungrae Park.
1. **[ByT5](model_doc/byt5)** (from Google Research) released with the paper [ByT5: Towards a token-free future with pre-trained byte-to-byte models](https://arxiv.org/abs/2105.13626) by Linting Xue, Aditya Barua, Noah Constant, Rami Al-Rfou, Sharan Narang, Mihir Kale, Adam Roberts, Colin Raffel.
1. **[CamemBERT](model_doc/camembert)** (from Inria/Facebook/Sorbonne) released with the paper [CamemBERT: a Tasty French Language Model](https://arxiv.org/abs/1911.03894) by Louis Martin*, Benjamin Muller*, Pedro Javier Ortiz Suárez*, Yoann Dupont, Laurent Romary, Éric Villemonte de la Clergerie, Djamé Seddah and Benoît Sagot.
1. **[CANINE](model_doc/canine)** (from Google Research) released with the paper [CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation](https://arxiv.org/abs/2103.06874) by Jonathan H. Clark, Dan Garrette, Iulia Turc, John Wieting.
@@ -288,6 +289,7 @@ Flax), PyTorch, dan/atau TensorFlow.
| BLIP-2 | ❌ | ❌ | ✅ | ❌ | ❌ |
| BLOOM | ❌ | ✅ | ✅ | ❌ | ❌ |
| BridgeTower | ❌ | ❌ | ✅ | ❌ | ❌ |
| Bros | ✅ | ✅ | ✅ | ❌ | ❌ |
| CamemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| CANINE | ✅ | ❌ | ✅ | ❌ | ❌ |
| Chinese-CLIP | ❌ | ❌ | ✅ | ❌ | ❌ |