* Fix generate_with_fallback **kwargs
* Change pop to get
* Delete keys from kwargs to prevent overriding generation_config
* Revert to passing kwargs by reference, but make a (shallow) copy
* dict -> copy.copy
* Add test_whisper_longform_multi_batch_beam
* Hard error when ignoring tensors. (#27484)
* [WIP] Hard error when ignoring tensors.
* Better selection/error when saving a checkpoint.
- Find all names we should normally drop (those are in the transformers
config)
- Find all disjoint tensors (for those we can safely trigger a copy to
get rid of the sharing before saving)
- Clone those disjoint tensors getting rid of the issue
- Find all identical names (those should be declared in the config
but we try to find them all anyway.)
- For all identical names:
- If they are in the config, just ignore them everything is fine
- If they are not, warn about them.
- For all remainder tensors which are shared yet neither identical NOR
disjoint. raise a hard error.
* Adding a failing test on `main` that passes here.
* We don't need to keep the subfolder logic in this test.
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Add small tests.
* Dead variable.
* Fixup.
* Fixing tied_Weights_keys on generic models.
* Fixup + T5 encoder/decoder tying (with different layers)
* Code quality.
* Dynamic member.
* trigger
* Fixing encoder name for other types of encoder/decoder combos.
* Fix scoping.
* Update .github/workflows/self-scheduled.yml
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Fixing the tied_weights after the call.
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix skip_special_tokens process for Wav2Vec2CTCTokenizer._decode
* Fix skip_special_tokens for Wav2Vec2CTCTokenizer._decode
* Exclude pad_token filtering since it is used as CTC-blank token
* Add small test for skip_special_tokens
* Update decoding test for added new token
* add FA2 to o.g Musicgen
* make style
* add FA2 support to Musicgen Melody
* add generation FA2 tests to o.g Musicgen
* make style and fix copies
* add Musicgen to FA2 docs + deprecate list
* add sdpa supports to Musicgen's
* make style and fix copies
* refactor attention implementation arguments
* add Copied from to sdpa tests
* add copied form in sdpa tests melody
* add copied for FA2 generation tests
* add FA2 inference copied from
* make style
* 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 09b70d7e4d.
* 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
* Start rework
* Fix failing test
* Include max
* Update src/transformers/trainer.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* 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
---------
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`
