[WIP] Tapas v4 (tres) (#9117)

* First commit: adding all files from tapas_v3 * Fix multiple bugs including soft dependency and new structure of the library * Improve testing by adding torch_device to inputs and adding dependency on scatter * Use Python 3 inheritance rather than Python 2 * First draft model cards of base sized models * Remove model cards as they are already on the hub * Fix multiple bugs with integration tests * All model integration tests pass * Remove print statement * Add test for convert_logits_to_predictions method of TapasTokenizer * Incorporate suggestions by Google authors * Fix remaining tests * Change position embeddings sizes to 512 instead of 1024 * Comment out positional embedding sizes * Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES * Added more model names * Fix truncation when no max length is specified * Disable torchscript test * Make style & make quality * Quality * Address CI needs * Test the Masked LM model * Fix the masked LM model * Truncate when overflowing * More much needed docs improvements * Fix some URLs * Some more docs improvements * Test PyTorch scatter * Set to slow + minify * Calm flake8 down * First commit: adding all files from tapas_v3 * Fix multiple bugs including soft dependency and new structure of the library * Improve testing by adding torch_device to inputs and adding dependency on scatter * Use Python 3 inheritance rather than Python 2 * First draft model cards of base sized models * Remove model cards as they are already on the hub * Fix multiple bugs with integration tests * All model integration tests pass * Remove print statement * Add test for convert_logits_to_predictions method of TapasTokenizer * Incorporate suggestions by Google authors * Fix remaining tests * Change position embeddings sizes to 512 instead of 1024 * Comment out positional embedding sizes * Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES * Added more model names * Fix truncation when no max length is specified * Disable torchscript test * Make style & make quality * Quality * Address CI needs * Test the Masked LM model * Fix the masked LM model * Truncate when overflowing * More much needed docs improvements * Fix some URLs * Some more docs improvements * Add add_pooling_layer argument to TapasModel Fix comments by @sgugger and @patrickvonplaten * Fix issue in docs + fix style and quality * Clean up conversion script and add task parameter to TapasConfig * Revert the task parameter of TapasConfig Some minor fixes * Improve conversion script and add test for absolute position embeddings * Improve conversion script and add test for absolute position embeddings * Fix bug with reset_position_index_per_cell arg of the conversion cli * Add notebooks to the examples directory and fix style and quality * Apply suggestions from code review * Move from `nielsr/` to `google/` namespace * Apply Sylvain's comments Co-authored-by: sgugger <sylvain.gugger@gmail.com> Co-authored-by: Rogge Niels <niels.rogge@howest.be> Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: sgugger <sylvain.gugger@gmail.com>
2020-12-15 23:08:49 +01:00
parent ad895af98d
commit 1551e2dc6d
22 changed files with 8497 additions and 78 deletions
--- a/README.md
+++ b/README.md
@@ -222,6 +222,7 @@ Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.
 ultilingual BERT into [DistilmBERT](https://github.com/huggingface/transformers/tree/master/examples/distillation) and a German version of DistilBERT.
 1. **[SqueezeBert](https://huggingface.co/transformers/model_doc/squeezebert.html)** released with the paper [SqueezeBERT: What can computer vision teach NLP about efficient neural networks?](https://arxiv.org/abs/2006.11316) by Forrest N. Iandola, Albert E. Shaw, Ravi Krishna, and Kurt W. Keutzer.
 1. **[T5](https://huggingface.co/transformers/model_doc/t5.html)** (from Google AI) released with the paper [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://arxiv.org/abs/1910.10683) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
+1. **[TAPAS](https://huggingface.co/transformers/master/model_doc/tapas.html)** released with the paper [TAPAS: Weakly Supervised Table Parsing via Pre-training](https://arxiv.org/abs/2004.02349) by Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno and Julian Martin Eisenschlos.
 1. **[Transformer-XL](https://huggingface.co/transformers/model_doc/transformerxl.html)** (from Google/CMU) released with the paper [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://arxiv.org/abs/1901.02860) by Zihang Dai*, Zhilin Yang*, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov.
 1. **[XLM](https://huggingface.co/transformers/model_doc/xlm.html)** (from Facebook) released together with the paper [Cross-lingual Language Model Pretraining](https://arxiv.org/abs/1901.07291) by Guillaume Lample and Alexis Conneau.
 1. **[XLM-ProphetNet](https://huggingface.co/transformers/model_doc/xlmprophetnet.html)** (from Microsoft Research) released with the paper [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://arxiv.org/abs/2001.04063) by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.