GitLab

* Logging

* Style

* hf_logging > utils.logging

* Address @thomwolf's comments

* Update test

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

* Revert bad change
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* start adding tie encoder to decoder functionality

* finish model tying

* make style

* Apply suggestions from code review

* fix t5 list including cross attention

* apply sams suggestions

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

* add max depth break point
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add cross attention layers for gpt2

* make gpt2 cross attention work

* finish bert2gpt2

* add explicit comments

* remove attention mask since not yet supported

* revert attn mask in pipeline

* Update src/transformers/modeling_gpt2.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* add encoder-decoder for roberta

* fix headmask

* apply Sylvains suggestions

* fix typo

* Apply suggestions from code review

* correct encoder decoder model

* Apply suggestions from code review

* apply sylvains suggestions

* Adding docs for how to load encoder_decoder pretrained model with individual config objects

* Adding docs for loading encoder_decoder config from pretrained folder

* Fixing  W293 blank line contains whitespace

* Update src/transformers/modeling_encoder_decoder.py

* Update src/transformers/modeling_encoder_decoder.py

* Update src/transformers/modeling_encoder_decoder.py

* Apply suggestions from code review

model file should only show examples for how to load save model

* Update src/transformers/configuration_encoder_decoder.py

* Update src/transformers/configuration_encoder_decoder.py

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

* Use return_dict=True in all tests

* Formatting

* 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>

* Moving rom transformers statements to relative imports in some files under src/

* Import order
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* [WIP] Proposal for model outputs

* All Bert models

* Make CI green maybe?

* Fix ONNX test

* Isolate ModelOutput from pt and tf

* Formatting

* Add Electra models

* Auto-generate docstrings from outputs

* Add TF outputs

* Add some BERT models

* Revert TF side

* Remove last traces of TF changes

* Fail with a clear error message

* Add Albert and work through Bart

* Add CTRL and DistilBert

* Formatting

* Progress on Bart

* Renames and finish Bart

* Formatting

* Fix last test

* Add DPR

* Finish Electra and add FlauBERT

* Add GPT2

* Add Longformer

* Add MMBT

* Add MobileBert

* Add GPT

* Formatting

* Add Reformer

* Add Roberta

* Add T5

* Add Transformer XL

* Fix test

* Add XLM + fix XLMForTokenClassification

* Style + XLMRoberta

* Add XLNet

* Formatting

* Add doc of return_tuple arg

* Refactor code samples

* Test docstrings

* Style

* Tokenization examples

* Run rust of tests

* First step to testing source docs

* Style and BART comment

* Test the remainder of the code samples

* Style

* let to const

* Formatting fixes

* Ready for merge

* Fix fixture + Style

* Fix last tests

* Update docs/source/quicktour.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Addressing @sgugger's comments + Fix MobileBERT in TF
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* moving logits post-processing out of beam search

* moving logits post-processing out of beam search

* first step cache

* fix_Encoder_Decoder

* patrick_version_postprocess

* add_keyword_arg

* first commit

* add new auto models

* better naming

* fix bert automodel

* fix automodel for pretraining

* add models to init

* fix name typo

* fix typo

* better naming

* future warning instead of depreciation warning

* Split LMBert model in two

* Fix example

* Remove lm_labels

* Adapt tests, refactor prepare_for_generation

* Fix merge

* Hide BeartLMHeadModel

* Deprecate masked_lm_labels argument

* Apply to all models

* Better error message

* fix bug

* add more tests

* change encoder decoder style to bart & t5 style

* make encoder decoder generation dummy work for bert

* make style

* clean init config in encoder decoder

* add tests for encoder decoder models

* refactor and add last tests

* refactor and add last tests

* fix attn masks for bert encoder decoder

* make style

* refactor prepare inputs for Bert

* refactor

* finish encoder decoder

* correct typo

* add docstring to config

* finish

* add tests

* better naming

* make style

* fix flake8

* clean docstring

* make style

* rename

* Results same as fairseq
* Wrote a ton of tests
* Struggled with api signatures
* added some docs

This should stabilize formatting.

This prevents transformers from being importable simply because the CWD
is the root of the git repository, while not being importable from other
directories. That led to inconsistent behavior, especially in examples.

Once you fetch this commit, in your dev environment, you must run:

    $ pip uninstall transformers
    $ pip install -e .

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.

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.

- Create the output directory (whose name is passed by the user in the "save_directory" parameter) where it will be saved encoder and decoder, if not exists.
- Empty the output directory, if it contains any files or subdirectories.
- Create the "encoder" directory inside "save_directory", if not exists.
- Create the "decoder" directory inside "save_directory", if not exists.
- Save the encoder and the decoder in the previous two directories, respectively.