* fix issue with logit processor in beam search in Flax
* adding FlaxNoRepeatNGramLogitsProcessor class + unit test
* style correction and code verification
* add FlaxNoRepeatNGramLogitsProcessor to the test_processor_list and test_processor_list_jitted tests
* fix an issue where ngrams are banned only if they appear ==1 time + update description of get_previous_ngrams
* replace non-jit compatible masking of ngrams that are not yet generated with jittable version
* Revert "fix issue with logit processor in beam search in Flax"
This reverts commit 09b70d7e4dc32d0cc4db61af09a835a9cd238b50.
* add FlaxNoRepeatNGramLogitsProcessor to _get_logits_processor
* change the method of casting to boolean of banned tokens indices
* fix code style
* remove some useless operations + significantly faster computation of update indices using jax.lax.fori_loop
* remove useless loop iterations
* set some variables that were calculated and used multiple times
* fix format
* Fix sinusoidal_embeddings in FlaubertModel
* Fix for Informer
* Fix for XLM
* Move sinusoidal emb for XLM
* Move sinusoidal emb for Flaubert
* Small cleanup
* Add comments on tests code copied from
* Add with Distilbert->
* fix bug and add tests
* nit
* otherway to get the cur len instead of attention mask
* more places where this might have been broken
* nit
* oups
* inputs_embeds vs input_embeds
* test generated outptus
* style
* nit
* fix
* skip failing biogpt
* add functions to get number of params which require grad, get optimizer group for parameters and get learning rates of param groups to trainer.py
* add tests and raise ValueError when optimizer is None
* add second layer to test and freeze its weigths
* check if torch is available before running tests
* use decorator to check if torch is available
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix test indentation
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
* Automatic safetensors conversion when lacking these files (#29390)
* Automatic safetensors conversion when lacking these files
* Remove debug
* Thread name
* Typo
* Ensure that raises do not affect the main thread
* Catch all errors
* Check for requires_grad when initing weights
* Add unit test
* Move sinusoidal positional encoding generation after post_init()
* Add modules to skip init list
* Move create_sinusoidal_embeddings to _init_weights
* add support for qwen2 MoE models
* update docs
* add support for qwen2 MoE models
* update docs
* update model name & test
* update readme
* update class names & readme & model_doc of Qwen2MoE.
* update architecture name
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* update modeling_qwen2_moe.py
* fix model architecture
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* update modeling_qwen2_moe.py
* fix model architecture
* fix style
* fix test when there are sparse and non sparse layers
* fixup
* Update README.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixup
* fixup
* add archive back
* add support for qwen2 MoE models
* update docs
* update model name & test
* update readme
* update class names & readme & model_doc of Qwen2MoE.
* update architecture name
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* update modeling_qwen2_moe.py
* fix model architecture
* fixup
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* fix style
* fix test when there are sparse and non sparse layers
* fixup
* add archive back
* fix integration test
* fixup
---------
Co-authored-by: bozheng-hit <dsoul0621@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* replace the 'decord' with 'av' in VideoClassificationPipeline
* fix the check of backend in VideoClassificationPipeline
* adjust the order of imports
* format 'video_classification.py'
* format 'video_classification.py' with ruff
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Co-authored-by: wanqiancheng <13541261013@163.com>
* add warnings if training args differ from checkpoint args stored in trainer_state.json
* run formatting and styling
* add a test
* format and styling
---------
Co-authored-by: Jonathan Flynn <jonl.flynn@guardian.co.uk>
* attempt to fix
* the actual fix that works with compilation!
* this?
* temporary update
* nit?
* dispatcg to memory efficient?
* update both models that have static cache support
* fix copies fix compile
* make sure fix
* fix cohere and gemma
* fix beams?
* nit
* slipped through the cracks
* nit
* nits
* update
* fix-copies
* skip failing tests
* nits
* Initial commit (still lots of unfinished bits)
* (Still untested) add safetensors sharding to save_pretrained
* Fix savetensors saving, update default shard size to match PT
* Add proper loading of TF-format safetensors
* Revert default size in case that changes things
* Fix incorrect index name
* Update loading priority
* Update tests
* Make the tests a little more stringent
* Expand tests
* Add sharded cross-test
* Fix argument name
* One more test fix
* Adding mlx to the list of allowed formats
* Remove irrelevant block for safetensors
* Refactor warning logging into a separate function
* Remove unused skip_logger_warnings arg
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Move function def
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Added SuperPoint docs
* Added tests
* Removed commented part
* Commit to create and fix add_superpoint branch with a new branch
* Fixed dummy_pt_objects
* Committed missing files
* Fixed README.md
* Apply suggestions from code review
Fixed small changes
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Moved ImagePointDescriptionOutput from modeling_outputs.py to modeling_superpoint.py
* Removed AutoModelForKeypointDetection and related stuff
* Fixed inconsistencies in image_processing_superpoint.py
* Moved infer_on_model logic simply in test_inference
* Fixed bugs, added labels to forward method with checks whether it is properly a None value, also added tests about this logic in test_modeling_superpoint.py
* Added tests to SuperPointImageProcessor to ensure that images are properly converted to grayscale
* Removed remaining mentions of MODEL_FOR_KEYPOINT_DETECTION_MAPPING
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fixed from (w, h) to (h, w) as input for tests
* Removed unnecessary condition
* Moved last_hidden_state to be the first returned
* Moved last_hidden_state to be the first returned (bis)
* Moved last_hidden_state to be the first returned (ter)
* Switched image_width and image_height in tests to match recent changes
* Added config as first SuperPointConvBlock init argument
* Reordered README's after merge
* Added missing first config argument to SuperPointConvBlock instantiations
* Removed formatting error
* Added SuperPoint to README's de, pt-br, ru, te and vi
* Checked out README_fr.md
* Fixed README_fr.md
* Test fix README_fr.md
* Test fix README_fr.md
* Last make fix-copies !
* Updated checkpoint path
* Removed unused SuperPoint doc
* Added missing image
* Update src/transformers/models/superpoint/modeling_superpoint.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Removed unnecessary import
* Update src/transformers/models/superpoint/modeling_superpoint.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Added SuperPoint to _toctree.yml
---------
Co-authored-by: steven <steven.bucaillle@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Steven Bucaille <steven.bucaille@buawei.com>
* use user_defined_symbols
* fixup
* nit
* add a very robust test
* make sure all models are tested with the `pretrained_tokenizer_to_test`
* should we make sure we test all of them?
* merge
* remove the id
* fix test
* update
* ousies
* oups
* fixup
* fix copies check
* remove `pretrained_tokenizer_to_test`
* add galore v1
* add import
* add tests and doc
* fix doctest
* forward contrib credits from discussions
* forward contrib credits from discussions
* Apply suggestions from code review
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
* fix failing tests'
* switch to `optim_target_modules` and clarify docs
* more clarification
* enhance lookup logic
* update a test to add peak memory
* add regex, all-linear and single string support
* add layer-wise optimization through DummyOptimizers and LRSchedulers
* forward contrib credits from discussions and original idea
* add a section about DDP not supported in layerwise
* Update src/transformers/trainer.py
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
* fix self
* check only if layer_wise
* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* oops
* make use of intervals
* clarify comment
* add matching tests
* GaLoRe -> GaLore
* move to `get_scheduler`
* add note on docs
* add a warning
* adapt a bit the docs
* update docstring
* support original API
* Update docs/source/en/trainer.md
* slightly refactor
* Update docs/source/en/trainer.md
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix args parsing and add tests
* remove warning for regex
* fix type hint
* add note about extra args
* make `is_regex` return optional
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Co-authored-by: Maxime <maximegmd @users.noreply.github.com>
Co-authored-by: Wing Lian <winglian @users.noreply.github.com>
Co-authored-by: Zach Mueller <muellerzr@gmail.com>
Co-authored-by: hiyouga <hiyouga@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
* Cohere Model Release (#1)
Cohere Model Release
* Remove unnecessary files and code (#2)
Some cleanup
* Delete cohere-model directory (#3)
* Make Fix (#5)
* Pr fixes (#6)
* fixes for pr
* pr fixes for the format
* pr fixes for the format
* src/transformers/models/auto/tokenization_auto.py
* Tokenizer test (#8)
* tokenizer test
* format fix
* Adding Docs and other minor changes (#7)
* Add modeling tests (#9)
* Smol Fix (#11)
* tokenization tests are fixed
* format fixes
* fix pr doc tests
* fix pr doc tests
* fix pr doc tests
* fix pr style check
* small changes in cohere.md
* FIX: Address final comments for transformers integration (#13)
* fix modeling final nits and add proper test file
* for now leave empty tests
* add integration test
* push new test
* fix modeling cohere (#14)
* Update chat templates to use the new API (#15)
---------
Co-authored-by: ahmetustun <ahmetustun89@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
