- 17 Dec, 2020 3 commits
- 16 Dec, 2020 1 commit
-
-
Patrick von Platen authored
* save intermediate * save intermediate * save intermediate * correct flax bert model file * new module / model naming * make style * almost finish BERT * finish roberta * make fix-copies * delete keys file * last refactor * fixes in run_mlm_flax.py * remove pooled from run_mlm_flax.py` * fix gelu | gelu_new * remove Module from inits * splits * dirty print * preventing warmup_steps == 0 * smaller splits * make fix-copies * dirty print * dirty print * initial_evaluation argument * declaration order fix * proper model initialization/loading * proper initialization * run_mlm_flax improvements: improper model inputs bugfix + automatic dataset splitting + tokenizers parallelism warning + avoiding warmup_steps=0 bug * removed tokenizers warning hack, fixed model re-initialization * reverted training_args.py changes * fix flax from pretrained * improve test in flax * apply sylvains tips * update init * make 0.3.0 compatible * revert tevens changes * revert tevens changes 2 * finalize revert * fix bug * add docs * add pretrained to init * Update src/transformers/modeling_flax_utils.py * fix copies * final improvements Co-authored-by:TevenLeScao <teven.lescao@gmail.com>
-
- 15 Dec, 2020 1 commit
-
-
Julien Plu authored
* Fix tests for TF 2.4 * Remove <2.4 limitation * Add version condition * Update tests/test_optimization_tf.py Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update tests/test_optimization_tf.py Co-authored-by:
-
- 14 Dec, 2020 2 commits
-
-
Sylvain Gugger authored
-
Sylvain Gugger authored
-
- 07 Dec, 2020 1 commit
-
-
Sylvain Gugger authored
* Add copyright everywhere missing * Style
-
- 30 Nov, 2020 2 commits
-
-
LysandreJik authored
-
LysandreJik authored
-
- 27 Nov, 2020 1 commit
-
-
Julien Plu authored
enforce unix newline encoding regardless of OS creating the file
-
- 24 Nov, 2020 1 commit
-
-
Stas Bekman authored
* implement support for run-time dependency version checking * try not escaping ! * use findall that works on py36 * small tweaks * autoformatter worship * simplify * shorter names * add support for non-versioned checks * add deps * revert * tokenizers not required, check version only if installed * make a proper distutils cmd and add make target * tqdm must be checked before tokenizers * workaround the DistributionNotFound peculiar setup * handle the rest of packages in setup.py * fully sync setup.py's install_requires - to check them all * nit * make install_requires more readable * typo * Update setup.py Co-authored-by:
-
- 19 Nov, 2020 1 commit
-
-
LysandreJik authored
-
- 16 Nov, 2020 1 commit
-
-
Sylvain Gugger authored
-
- 15 Nov, 2020 1 commit
-
-
Thomas Wolf authored
[breaking|pipelines|tokenizers] Adding slow-fast tokenizers equivalence tests pipelines - Removing sentencepiece as a required dependency (#8073) * Fixing roberta for slow-fast tests * WIP getting equivalence on pipelines * slow-to-fast equivalence - working on question-answering pipeline * optional FAISS tests * Pipeline Q&A * Move pipeline tests to their own test job again * update tokenizer to add sequence id methods * update to tokenizers 0.9.4 * set sentencepiecce as optional * clean up squad * clean up pipelines to use sequence_ids * style/quality * wording * Switch to use_fast = True by default * update tests for use_fast at True by default * fix rag tokenizer test * removing protobuf from required dependencies * fix NER test for use_fast = True by default * fixing example tests (Q&A examples use slow tokenizers for now) * protobuf in main deps extras["sentencepiece"] and example deps * fix protobug install test * try to fix seq2seq by switching to slow tokenizers for now * Update src/transformers/tokenization_utils_base.py Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> * Update src/transformers/tokenization_utils_base.py Co-authored-by:
-
- 13 Nov, 2020 1 commit
-
-
Lysandre Debut authored
* Model templates * TensorFlow * Remove pooler * CI * Tokenizer + Refactoring * Encoder-Decoder * Let's go testing * Encoder-Decoder in TF * Let's go testing in TF * Documentation * README * Fixes * Better names * Style * Update docs * Choose to skip either TF or PT * Code quality fixes * Add to testing suite * Update file path * Cookiecutter path * Update `transformers` path * Handle rebasing * Remove seq2seq from model templates * Remove s2s config * Apply Sylvain and Patrick comments * Apply suggestions from code review Co-authored-by:
-
- 10 Nov, 2020 1 commit
-
-
Lysandre authored
-
- 09 Nov, 2020 1 commit
-
-
Sylvain Gugger authored
-
- 04 Nov, 2020 1 commit
-
-
Sylvain Gugger authored
* Try -j option * Try other thing * Bigger machine * Test lower sphinx version * Remove trailing space
-
- 27 Oct, 2020 3 commits
-
-
Sylvain Gugger authored
-
Jason Wolosonovich authored
Co-authored-by: -
Stas Bekman authored
-
- 20 Oct, 2020 1 commit
-
-
Lysandre authored
-
- 19 Oct, 2020 1 commit
-
-
Funtowicz Morgan authored
* WIP flax bert * Initial commit Bert Jax/Flax implementation. * Embeddings working and equivalent to PyTorch. * Move embeddings in its own module BertEmbeddings * Added jax.jit annotation on forward call * BertEncoder on par with PyTorch ! :D * Add BertPooler on par with PyTorch !! * Working Jax+Flax implementation of BertModel with < 1e-5 differences on the last layer. * Fix pooled output to take only the first token of the sequence. * Refactoring to use BertConfig from transformers. * Renamed FXBertModel to FlaxBertModel * Model is now initialized in FlaxBertModel constructor and reused. * WIP JaxPreTrainedModel * Cleaning up the code of FlaxBertModel * Added ability to load Flax model saved through save_pretrained() * Added ability to convert Pytorch Bert model to FlaxBert * FlaxBert can now load every Pytorch Bert model with on-the-fly conversion * Fix hardcoded shape values in conversion scripts. * Improve the way we handle LayerNorm conversion from PyTorch to Flax. * Added positional embeddings as parameter of BertModel with default to np.arange. * Let's roll FlaxRoberta ! * Fix missing position_ids parameters on predict for Bert * Flax backend now supports batched inputs Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Make it possible to load msgpacked model on convert from pytorch in last resort. Signed-off-by:
Stefan Schweter <stefan@schweter.it> * Attempt to make style * Attempt to make style in tests too * Added jax & jaxlib to the flax optional dependencies. * Attempt to fix flake8 warnings ... * Redo black again and again * When black and flake8 fight each other for a space ...
馃挜 馃挜 馃挜 * Try removing trailing comma to make both black and flake happy! * Fix invalid is_<framework>_available call, thanks @LysandreJik馃帀 * Fix another invalid import in flax_roberta test * Bump and pin flax release to 0.1.0. * Make flake8 happy, remove unused jax import * Change the type of the catch for msgpack. * Remove unused import. * Put seed as optional constructor parameter. * trigger ci again * Fix too much parameters in BertAttention. * Formatting. * Simplify Flax unittests to avoid machine crashes. * Fix invalid number of arguments when raising issue for an unknown model. * Address @bastings comment in PR, moving jax.jit decorated outside of __call__ * Fix incorrect path to require_flax/require_pytorch functions. Signed-off-by:Morgan Funtowicz <funtowiczmo@gmail.com> * Attempt to make style. Signed-off-by:
馃幎 Signed-off-by:Marc van Zee <marcvanzee@gmail.com> * Bump flax to it's latest version Co-authored-by:
-
- 18 Oct, 2020 1 commit
-
-
Thomas Wolf authored
* splitting fast and slow tokenizers [WIP] * [WIP] splitting sentencepiece and tokenizers dependencies * update dummy objects * add name_or_path to models and tokenizers * prefix added to file names * prefix * styling + quality * spliting all the tokenizer files - sorting sentencepiece based ones * update tokenizer version up to 0.9.0 * remove hard dependency on sentencepiece
馃帀 * and removed hard dependency on tokenizers馃帀 * update conversion script * update missing models * fixing tests * move test_tokenization_fast to main tokenization tests - fix bugs * bump up tokenizers * fix bert_generation * update ad fix several tokenizers * keep sentencepiece in deps for now * fix funnel and deberta tests * fix fsmt * fix marian tests * fix layoutlm * fix squeezebert and gpt2 * fix T5 tokenization * fix xlnet tests * style * fix mbart * bump up tokenizers to 0.9.2 * fix model tests * fix tf models * fix seq2seq examples * fix tests without sentencepiece * fix slow => fast conversion without sentencepiece * update auto and bert generation tests * fix mbart tests * fix auto and common test without tokenizers * fix tests without tokenizers * clean up tests lighten up when tokenizers + sentencepiece are both off * style quality and tests fixing * add sentencepiece to doc/examples reqs * leave sentencepiece on for now * style quality split hebert and fix pegasus * WIP Herbert fast * add sample_text_no_unicode and fix hebert tokenization * skip FSMT example test for now * fix style * fix fsmt in example tests * update following Lysandre and Sylvain's comments * Update src/transformers/testing_utils.py Co-authored-by:
-
- 09 Oct, 2020 5 commits
-
-
Doug Blank authored
* Import intergration libraries first * isort and black happiness * flake8 happiness * Add a test * Black reformat * Ignore import order in tests * A heavy-handed method of disabling comet for tests * Remove comet_ml tests * Run black on setup.py
-
sgugger authored
-
Sylvain Gugger authored
-
-
sgugger authored
-
- 08 Oct, 2020 1 commit
-
-
Thomas Wolf authored
Adding Fast tokenizers for SentencePiece based tokenizers - Breaking: remove Transfo-XL fast tokenizer (#7141) * [WIP] SP tokenizers * fixing tests for T5 * WIP tokenizers * serialization * update T5 * WIP T5 tokenization * slow to fast conversion script * Refactoring to move tokenzier implementations inside transformers * Adding gpt - refactoring - quality * WIP adding several tokenizers to the fast world * WIP Roberta - moving implementations * update to dev4 switch file loading to in-memory loading * Updating and fixing * advancing on the tokenizers - updating do_lower_case * style and quality * moving forward with tokenizers conversion and tests * MBart, T5 * dumping the fast version of transformer XL * Adding to autotokenizers + style/quality * update init and space_between_special_tokens * style and quality * bump up tokenizers version * add protobuf * fix pickle Bert JP with Mecab * fix newly added tokenizers * style and quality * fix bert japanese * fix funnel * limite tokenizer warning to one occurence * clean up file * fix new tokenizers * fast tokenizers deep tests * WIP adding all the special fast tests on the new fast tokenizers * quick fix * adding more fast tokenizers in the fast tests * all tokenizers in fast version tested * Adding BertGenerationFast * bump up setup.py for CI * remove BertGenerationFast (too early) * bump up tokenizers version * Clean old docstrings * Typo * Update following Lysandre comments Co-authored-by:Sylvain Gugger <sylvain.gugger@gmail.com>
-
- 30 Sep, 2020 1 commit
-
-
Sylvain Gugger authored
-
- 29 Sep, 2020 1 commit
-
-
Sylvain Gugger authored
-
- 28 Sep, 2020 1 commit
-
-
Lysandre authored
-
- 22 Sep, 2020 2 commits
-
-
Ola Piktus authored
* added rag WIP * path fix * Formatting / renaming prior to actual work * added rag WIP * path fix * Formatting / renaming prior to actual work * added rag WIP * path fix * Formatting / renaming prior to actual work * added rag WIP * Formatting / renaming prior to actual work * First commit * improve comments * Retrieval evaluation scripts * refactor to include modeling outputs + MPI retriever * Fix rag-token model + refactor * Various fixes + finetuning logic * use_bos fix * Retrieval refactor * Finetuning refactoring and cleanup * Add documentation and cleanup * Remove set_up_rag_env.sh file * Fix retrieval wit HF index * Fix import errors * Fix quality errors * Refactor as per suggestions in https://github.com/huggingface/transformers/pull/6813#issuecomment-687208867 * fix quality * Fix RAG Sequence generation * minor cleanup plus initial tests * fix test * fix tests 2 * Comments fix * post-merge fixes * Improve readme + post-rebase refactor * Extra dependencied for tests * Fix tests * Fix tests 2 * Refactor test requirements * Fix tests 3 * Post-rebase refactor * rename nlp->datasets * RAG integration tests * add tokenizer to slow integration test and allow retriever to run on cpu * add tests; fix position ids warning * change structure * change structure * add from encoder generator * save working solution * make all integration tests pass * add RagTokenizer.save/from_pretrained and RagRetriever.save/from_pretrained * don't save paths * delete unnecessary imports * pass config to AutoTokenizer.from_pretrained for Rag tokenizers * init wiki_dpr only once * hardcode legacy index and passages paths (todo: add the right urls) * finalize config * finalize retriver api and config api * LegacyIndex index download refactor * add dpr to autotokenizer * make from pretrained more flexible * fix ragfortokengeneration * small name changes in tokenizer * add labels to models * change default index name * add retrieval tests * finish token generate * align test with previous version and make all tests pass * add tests * finalize tests * implement thoms suggestions * add first version of test * make first tests work * make retriever platform agnostic * naming * style * add legacy index URL * docstrings + simple retrieval test for distributed * clean model api * add doc_ids to retriever's outputs * fix retrieval tests * finish model outputs * finalize model api * fix generate problem for rag * fix generate for other modles * fix some tests * save intermediate * set generate to default * big refactor generate * delete rag_api * correct pip faiss install * fix auto tokenization test * fix faiss install * fix test * move the distributed logic to examples * model page * docs * finish tests * fix dependencies * fix import in __init__ * Refactor eval_rag and finetune scripts * start docstring * add psutil to test * fix tf test * move require torch to top * fix retrieval test * align naming * finish automodel * fix repo consistency * test ragtokenizer save/load * add rag model output docs * fix ragtokenizer save/load from pretrained * fix tokenizer dir * remove torch in retrieval * fix docs * fixe finetune scripts * finish model docs * finish docs * remove auto model for now * add require torch * remove solved todos * integrate sylvains suggestions * sams comments * correct mistake on purpose * improve README * Add generation test cases * fix rag token * clean token generate * fix test * add note to test * fix attention mask * add t5 test for rag * Fix handling prefix in finetune.py * don't overwrite index_name Co-authored-by:
Patrick Lewis <plewis@fb.com> Co-authored-by:
Aleksandra Piktus <piktus@devfair0141.h2.fair> Co-authored-by:
Aleksandra Piktus <piktus@learnfair5102.h2.fair> Co-authored-by:
Aleksandra Piktus <piktus@learnfair5067.h2.fair> Co-authored-by:
Your Name <you@example.com> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Quentin Lhoest <lhoest.q@gmail.com>
-
Lysandre authored
-
- 14 Sep, 2020 1 commit
-
-
sgugger authored
-
- 07 Sep, 2020 2 commits
-
-
Stas Bekman authored
my flake8 wasn't up-to-date enough `make quality` wasn't reporting the same things CI did - this PR adds the actual required version. Thinking more about some of these minimal versions - CI will always install afresh and thus will always run the latest version. Is there a way to tell pip to always install the latest versions of certain dependencies on `pip install -i ".[dev]"`, rather than hardcoding the minimals which quickly become outdated?
-
Stas Bekman authored
unittest doesn't support pytest's super-handy `@pytest.mark.parametrize`, I researched and there are many proposed workarounds, most tedious at best. If we include https://pypi.org/project/parameterized/ in dev dependencies - it will provide a very easy to write parameterization in tests. Same as pytest's fixture, plus quite a few other ways. Example: ``` from parameterized import parameterized @parameterized([ (2, 2, 4), (2, 3, 8), (1, 9, 1), (0, 9, 0), ]) def test_pow(base, exponent, expected): assert_equal(math.pow(base, exponent), expected) ``` (extra `self`var if inside a test class) To remind the pytest style is slightly different: ``` @pytest.mark.parametrize("test_input,expected", [("3+5", 8), ("2+4", 6), ("6*9", 42)]) def test_eval(test_input, expected): ``` More examples here: https://pypi.org/project/parameterized May I suggest that it will make it much easier to write some types of tests?
-
- 01 Sep, 2020 1 commit
-
-
Lysandre authored
-
