* try to stylify using ruff
* might need to remove these changes?
* use ruf format andruff check
* use isinstance instead of type comparision
* use # fmt: skip
* use # fmt: skip
* nits
* soem styling changes
* update ci job
* nits isinstance
* more files update
* nits
* more nits
* small nits
* check and format
* revert wrong changes
* actually use formatter instead of checker
* nits
* well docbuilder is overwriting this commit
* revert notebook changes
* try to nuke docbuilder
* style
* fix feature exrtaction test
* remve `indent-width = 4`
* fixup
* more nits
* update the ruff version that we use
* style
* nuke docbuilder styling
* leve the print for detected changes
* nits
* Remove file I/O
Co-authored-by: charliermarsh
<charlie.r.marsh@gmail.com>
* style
* nits
* revert notebook changes
* Add # fmt skip when possible
* Add # fmt skip when possible
* Fix
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* NIts
* more fixes
* fix tapas
* Another way to skip
* Recommended way
* Fix two more fiels
* Remove asynch
Remove asynch
---------
Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com>
* fix test for bart. Order is correct now let's skip BPEs
* ouf
* styling
* fix bert....
* slow refactoring
* current updates
* massive refactoring
* update
* NICE!
* update to see where I am at
* updates
* update
* update
* revert
* updates
* updates
* start supporting legacy_save
* styling
* big update
* revert some changes
* nits
* nniiiiiice
* small fixes
* kinda fix t5 with new behaviour
* major update
* fixup
* fix copies
* today's updates
* fix byt5
* upfate
* update
* update
* updates
* update vocab size test
* Barthez does not use not need the fairseq offset ids
* super calll must be after
* calll super
* move all super init
* move other super init
* fixup
* nits
* more fixes
* nits
* more fixes
* nits
* more fix
* remove useless files
* ouch all of them are affected
* and more!
* small imporvements
* no more sanitize token
* more changes around unique no split tokens
* partially fix more things
* keep legacy save but add warning
* so... more fixes
* updates
* guess deberta tokenizer could be nuked
* fixup
* fixup did some bad things
* nuke it if it breaks
* remove prints and pretrain fast from slow with new format.
* fixups
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fiou
* nit
* by default specials should not be normalized?
* update
* remove brakpoint
* updates
* a lot of updates
* fixup
* fixes revert some changes to match fast
* small nits
* that makes it cleaner
* fix camembert accordingly
* update
* some lest breaking changes
* update
* fixup
* fix byt5 and whisper mostly
* some more fixes, canine's byte vocab
* fix gpt2
* fix most of the perceiver tests (4 left)
* fix layout lmv3
* fixup
* fix copies for gpt2 style
* make sure to only warn once
* fix perciever and gpt2 tests
* some more backward compatibility: also read special tokens map because some ppl use it........////.....
* fixup
* add else when reading
* nits
* fresh updates
* fix copies
* will this make everything faster?
* fixes
* more fixes
* update
* more fixes
* fixup
* is the source of truth right?
* sorry camembert for the troubles
* current updates
* fixup
* update led
* update
* fix regression
* fix single word
* more model specific fixes
* fix t5 tests
* fixup
* more comments
* update
* fix nllb
* rstrip removed
* small fixes
* better handle additional_special_tokens and vocab sizes
* fixing
* styling
* fix 4 / 21
* fixup
* fix nlbb's tests
* some fixes
* fix t5
* fixes
* style
* fix canine tests
* damn this is nice
* nits
* m2m100 nit
* fixups
* fixes!
* fixup
* stash
* fix merge
* revert bad change
* fixup
* correct order for code Llama
* fix speecht5 post merge
* styling
* revert source of 11 fails
* small nits
* all changes in one go
* fnet hack
* fix 2 more tests
* update based on main branch of tokenizers
* fixup
* fix VITS issues
* more fixes
* fix mgp test
* fix camembert issues
* oups camembert still has 2 failing tests
* mluke fixes
* decode fixes
* small nits
* nits
* fix llama and vits
* fix camembert
* smal nits
* more fixes when initialising a fast from a slow and etc
* fix one of the last test
* fix CPM tokenizer test
* fixups
* fix pop2piano
* fixup
* ⚠️ Change tokenizers required version ⚠️
* ⚠️ Change tokenizers required version ⚠️
* "tokenizers>=0.14,<0.15", don't forget smaller than
* fix musicgen tests and pretraiendtokenizerfast
* fix owlvit and all
* update t5
* fix 800 red
* fix tests
* fix the fix of the fix of t5
* styling
* documentation nits
* cache _added_tokens_encoder
* fixups
* Nit
* fix red tests
* one last nit!
* make eveything a lot simpler
* Now it's over 😉
* few small nits
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* updates that work for now
* tests that should no be skipped / changed and fixed next
* fixup
* i am ashamed
* pushe the fix
* update
* fixups
* nits
* fix added_tokens_encoder
* fix canine test
* fix pegasus vocab
* fix transfoXL
* fixup
* whisper needs to be fixed for train new
* pegasus nits
* more pegasus fixes
* minor update
* better error message in failed test
* fix whisper failing test
* fix whisper failing test
* fix pegasus
* fixup
* fix **** pegasus
* reset things
* remove another file
* attempts to fix the strange custome encoder and offset
* nits here and there
* update
* fixup
* nit
* fix the whisper test
* nits nits
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* updates based on review
* some small update to potentially remove
* nits
* import rlu cache
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Lysandre Debut <hi@lysand.re>
* move warning to `from_pretrained`
* update tests results now that the special tokens are always added
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>
* hidden layers, huh, what are they good for (absolutely nothing)
* Some tests break with 1 hidden layer, use 2
* Use 1 hidden layer in a few slow models
* Use num_hidden_layers=2 everywhere
* Slightly higher tol for groupvit
* Slightly higher tol for groupvit
* Fix TypeError: Object of type int64 is not JSON serializable
* Convert numpy.float64 and numpy.int64 to float and int for json serialization
* Black reformatted examples/pytorch/token-classification/run_ner_no_trainer.py
* * make style
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor
* Don't forget the imports
* Add the imports to tests too
* make fixup
* Refactor tests that depended on get_type_hints
* Better test refactor
* Fix an old hidden bug in the test_keras_fit input creation code
* Fix for the Deit tests
* Fix inverted conditional in TF common test!
* Make the same change in the PT tests file
* Make sure hidden states for GPT2 have the same output shape in PT/TF
* Minor fix to PT implementation of token classification loss
* Skip loss equivalence test for TFHubert because it keeps overflowing to inf
* Compute LM loss for TF the (weird) way it's computed in PT
* Skip loss equivalence test for Wav2Vec2 for the same reason as Hubert
* Fix - don't try to access the hidden states property when output is a tuple
* time to say goodbye, torch 1.7 and 1.8
* clean up torch_int_div
* clean up is_torch_less_than_1_8-9
* update
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* rounding_mode = "floor" instead of // to prevent behavioral change
* add other TODO
* use `torch_int_div` from pytrch_utils
* same for tests
* fix copies
* style
* use relative imports when needed
* Co-authored-by: sgugger <sylvain.gugger@gmail.com>
* Result of black 23.1
* Update target to Python 3.7
* Switch flake8 to ruff
* Configure isort
* Configure isort
* Apply isort with line limit
* Put the right black version
* adapt black in check copies
* Fix copies
* torch.jit._state
* Fix past CI
* Fix for perceiver
* Fix REALM
* Fix for Bloom
* Fix for SwinMode
* Fix for TrajectoryTransformerModel
* Fix for test_wav2vec2_with_lm
* make style
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Clean up deprecation warnings
Notes:
Changed some strings in tests to raw strings, which will change the literal content of the strings as they are fed into whatever machine handles them.
Test cases for past in the past/past_key_values switch changed/removed due to warning of impending removal
* Add PILImageResampling abstraction for PIL.Image.Resampling
* Fix train_step and test_step, correctly enable CLIP fit test
* Stop using get_args on older Python versions
* Don't use get_origin either
* UnionType is actually even newer, don't use that either
* Apply the same fix to test_loss_computation
* Just realized I was accidentally skipping a bunch of tests!
* Fix test_loss_computation for models without separable labels
* Fix scalar losses in test_step and train_step
* Stop committing your breakpoints
* Fix Swin loss shape
* Fix Tapas loss shape
* Shape fixes for TAPAS, DeIT, HuBERT and ViTMAE
* Add loss computation to TFMobileBertForPreTraining
* make fixup and move copied from statement
* make fixup and move copied from statement
* Correct copied from
* Add labels and next_sentence_label inputs to TFMobileBERT
* Make sure total_loss is always defined
* Update tests/test_modeling_tf_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fix copied from
* Ensure CTC models get labels in tests
* Ensure CTC models get labels in tests
* Fix tests for vit_mae
* Fix tests for vit_mae
* Fix tests for vit_mae
* Reduce batch size for wav2vec2 testing because it was causing OOM
* Skip some TAPAS tests that are failing
* Skip a failing HuBERT test
* make style
* Fix mobilebertforpretraining test
* Skip Wav2Vec2 tests that use huge amounts of mem
* Skip keras_fit for Wav2Vec2 as well
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
