GitLab

* configuration_squeezebert.py

thin wrapper around bert tokenizer

fix typos

wip sb model code

wip modeling_squeezebert.py. Next step is to get the multi-layer-output interface working

set up squeezebert to use BertModelOutput when returning results.

squeezebert documentation

formatting

allow head mask that is an array of [None, ..., None]

docs

docs cont'd

path to vocab

docs and pointers to cloud files (WIP)

line length and indentation

squeezebert model cards

formatting of model cards

untrack modeling_squeezebert_scratchpad.py

update aws paths to vocab and config files

get rid of stub of NSP code, and advise users to pretrain with mlm only

fix rebase issues

redo rebase of modeling_auto.py

fix issues with code formatting

more code format auto-fixes

move squeezebert before bert in tokenization_auto.py and modeling_auto.py because squeezebert inherits from bert

tests for squeezebert modeling and tokenization

fix typo

move squeezebert before bert in modeling_auto.py to fix inheritance problem

disable test_head_masking, since squeezebert doesn't yet implement head masking

fix issues exposed by the test_modeling_squeezebert.py

fix an issue exposed by test_tokenization_squeezebert.py

fix issue exposed by test_modeling_squeezebert.py

auto generated code style improvement

issue that we inherited from modeling_xxx.py: SqueezeBertForMaskedLM.forward() calls self.cls(), but there is no self.cls, and I think the goal was actually to call self.lm_head()

update copyright

resolve failing 'test_hidden_states_output' and remove unused encoder_hidden_states and encoder_attention_mask

docs

add integration test. rename squeezebert-mnli --> squeezebert/squeezebert-mnli

autogenerated formatting tweaks

integrate feedback from patrickvonplaten and sgugger to programming style and documentation strings

* tiny change to order of imports

* Clean RAG docs and template docs

* Fix typo

* Better doc

* remove the implied defaults to :obj:`None`

* fix bug in the original

* replace to :obj:`True`, :obj:`False`

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* Fixed empty asserts

* black-reformatted stragglers in templates

* More code quality checks

* Update src/transformers/convert_marian_to_pytorch.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/convert_marian_to_pytorch.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* removed unused line as per @sshleifer
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Switch from return_tuple to return_dict

* Fix test

* [WIP] Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleC… (#5614)

* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests

* AutoModels


Tiny tweaks

* Style

* Final changes before merge

* Re-order for simpler review

* Final fixes

* Addressing @sgugger's comments

* Test MultipleChoice

* Rework TF trainer (#6038)

* Fully rework training/prediction loops

* fix method name

* Fix variable name

* Fix property name

* Fix scope

* Fix method name

* Fix tuple index

* Fix tuple index

* Fix indentation

* Fix variable name

* fix eval before log

* Add drop remainder for test dataset

* Fix step number + fix logging datetime

* fix eval loss value

* use global step instead of step + fix logging at step 0

* Fix logging datetime

* Fix global_step usage

* Fix breaking loop + logging datetime

* Fix step in prediction loop

* Fix step breaking

* Fix train/test loops

* Force TF at least 2.2 for the trainer

* Use assert_cardinality to facilitate the dataset size computation

* Log steps per epoch

* Make tfds compliant with TPU

* Make tfds compliant with TPU

* Use TF dataset enumerate instead of the Python one

* revert previous commit

* Fix data_dir

* Apply style

* rebase on master

* Address Sylvain's comments

* Address Sylvain's and Lysandre comments

* Trigger CI

* Remove unused import

* Switch from return_tuple to return_dict

* Fix test

* Add recent model
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Julien Plu <plu.julien@gmail.com>

Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* DOC: Replace instances of ``config.output_attentions`` with function argument ``output_attentions``

* DOC: Apply Black Formatting

* Fix errors where output_attentions was undefined

* Remove output_attentions in classes per review

* Fix regressions on tests having `output_attention`

* Fix further regressions in tests relating to `output_attentions`

Ensure proper propagation of `output_attentions` as a function parameter
to all model subclasses

* Fix more regressions in `test_output_attentions`

* Fix issues with BertEncoder

* Rename related variables to `output_attentions`

* fix pytorch tests

* fix bert and gpt2 tf

* Fix most TF tests for `test_output_attentions`

* Fix linter errors and more TF tests

* fix conflicts

* DOC: Apply Black Formatting

* Fix errors where output_attentions was undefined

* Remove output_attentions in classes per review

* Fix regressions on tests having `output_attention`

* fix conflicts

* fix conflicts

* fix conflicts

* fix conflicts

* fix pytorch tests

* fix conflicts

* fix conflicts

* Fix linter errors and more TF tests

* fix tf tests

* make style

* fix isort

* improve output_attentions

* improve tensorflow
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Kill model archive maps

* Fixup

* Also kill model_archive_map for MaskedBertPreTrainedModel

* Unhook config_archive_map

* Tokenizers: align with model id changes

* make style && make quality

* Fix CI

* [file_utils] use_cdn + documentation

* Move to cdn. urls for weights

* [urls] Hotfix for bert-base-japanese

* Delete some copy pasted code

This change is mostly autogenerated with:

    $ python -m autoflake --in-place --recursive --remove-all-unused-imports --ignore-init-module-imports examples templates transformers utils hubconf.py setup.py

I made minor changes in the generated diff.

This change is mostly autogenerated with:

    $ python -m autoflake --in-place --recursive examples templates transformers utils hubconf.py setup.py

I made minor changes in the generated diff.

Ignore warnings related to Python 2, because it's going away soon.

Fixes flake8 warning W291 (x224).

This is the result of:

    $ isort --recursive examples templates transformers utils hubconf.py setup.py

This is the result of:

    $ black --line-length 119 examples templates transformers utils hubconf.py setup.py

There's a lot of fairly long lines in the project. As a consequence, I'm
picking the longest widely accepted line length, 119 characters.

This is also Thomas' preference, because it allows for explicit variable
names, to make the code easier to understand.