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Add DPR model (#5279)

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* 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>
This commit is contained in:
Quentin Lhoest
2020-07-07 14:56:12 +02:00
committed by GitHub
parent d2a9399115
commit fbd8792195
11 changed files with 1531 additions and 3 deletions
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4
src/transformers/tokenization_utils_base.py
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@@ -965,7 +965,7 @@ ENCODE_KWARGS_DOCSTRING = r"""
>= 7.5 (Volta).
return_tensors (:obj:`str`, `optional`, defaults to :obj:`None`):
Can be set to 'tf', 'pt' or 'np' to return respectively TensorFlow :obj:`tf.constant`,
PyTorch :obj:`torch.Tensor` or Numpy :oj: `np.ndarray` instead of a list of python integers.
PyTorch :obj:`torch.Tensor` or Numpy :obj: `np.ndarray` instead of a list of python integers.
"""
ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING = r"""
@@ -1900,7 +1900,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin):
return_attention_mask: (optional) Set to False to avoid returning attention mask (default: set to model specifics)
return_tensors (:obj:`str`, `optional`, defaults to :obj:`None`):
Can be set to 'tf', 'pt' or 'np' to return respectively TensorFlow :obj:`tf.constant`,
PyTorch :obj:`torch.Tensor` or Numpy :oj: `np.ndarray` instead of a list of python integers.
PyTorch :obj:`torch.Tensor` or Numpy :obj: `np.ndarray` instead of a list of python integers.
verbose (:obj:`bool`, `optional`, defaults to :obj:`True`):
Set to ``False`` to avoid printing infos and warnings.
"""