GitLab

* Create modeling_tf_dpr.py

* Add TFDPR

* Add back TFPegasus, TFMarian, TFMBart, TFBlenderBot

last commit accidentally deleted these 4 lines, so I recover them back

* Add TFDPR

* Add TFDPR

* clean up some comments, add TF input-style doc string

* Add TFDPR

* Make return_dict=False as default

* Fix return_dict bug (in .from_pretrained)

* Add get_input_embeddings()

* Create test_modeling_tf_dpr.py

The current version is already passed all 27 tests!
Please see the test run at : 
https://colab.research.google.com/drive/1czS_m9zy5k-iSJbzA_DP1k1xAAC_sdkf?usp=sharing



* fix quality

* delete init weights

* run fix copies

* fix repo consis

* del config_class, load_tf_weights

They shoud be 'pytorch only'

* add config_class back

after removing it, test failed ... so totally only removing "use_tf_weights = None" on Lysandre suggestion

* newline after .. note::

* import tf, np (Necessary for ModelIntegrationTest)

* slow_test from_pretrained with from_pt=True

At the moment we don't have TF weights (since we don't have official official TF model)
Previously, I did not run slow test, so I missed this bug

* Add simple TFDPRModelIntegrationTest

Note that this is just a test that TF and Pytorch gives approx. the same output.
However, I could not test with the official DPR repo's output yet

* upload correct tf model

* remove position_ids as missing keys
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patrickvonplaten <patrick@huggingface.co>

* add training tests

* correct longformer

* fix docs

* fix some tests

* fix some more train tests

* remove ipdb

* fix multiple edge case model training

* fix funnel and prophetnet

* clean gpt models

* undo renaming of albert

* fix distilbert

* fix typo

* improve unit tests

this is a sample of one test according to the request in https://github.com/huggingface/transformers/issues/5973
before I apply it to the rest

* batch 1

* batch 2

* batch 3

* batch 4

* batch 5

* style

* non-tf template

* last deletion of check_loss_output

* Use return_dict=True in all tests

* Formatting

* fix test imports

* fix max_length

* style

* fix tests

* beginning of dpr modeling

* wip

* implement forward

* remove biencoder + better init weights

* export dpr model to embed model for nlp lib

* add new api

* remove old code

* make style

* fix dumb typo

* don't load bert weights

* docs

* docs

* style

* move the `k` parameter

* fix init_weights

* add pretrained configs

* minor

* update config names

* style

* better config

* style

* clean code based on PR comments

* change Dpr to DPR

* fix config

* switch encoder config to a dict

* style

* inheritance -> composition

* add messages in assert startements

* add dpr reader tokenizer

* one tokenizer per model

* fix base_model_prefix

* fix imports

* typo

* add convert script

* docs

* change tokenizers conf names

* style

* change tokenizers conf names

* minor

* minor

* fix wrong names

* minor

* remove unused convert functions

* rename convert script

* use return_tensors in tokenizers

* remove n_questions dim

* move generate logic to tokenizer

* style

* add docs

* docs

* quality

* docs

* add tests

* style

* add tokenization tests

* DPR full tests

* Stay true to the attention mask building

* update docs

* missing param in bert input docs

* docs

* style
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>