* Fix model load when it has both code on the Hub and locally
* Add input check with timeout
* Add tests
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Some non-saved stuff
* Add feature extractors
* Add image processor
* Add model
* Add processor and tokenizer
* Reduce timeout
---------
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* A fun new PR where I break the entire codebase again
* A fun new PR where I break the entire codebase again
* Handle cross-attention
* Move calls to model(model.dummy_inputs) to the new build() method
* Seeing what fails with the build context thing
* make fix-copies
* Let's see what fails with new build methods
* Fix the pytorch crossload build calls
* Fix the overridden build methods in vision_text_dual_encoder
* Make sure all our build methods set self.built or call super().build(), which also sets it
* make fix-copies
* Remove finished TODO
* Tentatively remove unneeded (?) line
* Transpose b in deberta correctly and remove unused threading local
* Get rid of build_with_dummies and all it stands for
* Rollback some changes to TF-PT crossloading
* Correctly call super().build()
* Add test_backbone for convnext
* Add TimmBackbone model
* Add check for backbone type
* Tidying up - config checks
* Update convnextv2
* Tidy up
* Fix indices & clearer comment
* Exceptions for config checks
* Correclty update config for tests
* Safer imports
* Safer safer imports
* Fix where decorators go
* Update import logic and backbone tests
* More import fixes
* Fixup
* Only import all_models if torch available
* Fix kwarg updates in from_pretrained & main rebase
* Tidy up
* Add tests for AutoBackbone
* Tidy up
* Fix import error
* Fix up
* Install nattan in doc_test_job
* Revert back to setting self._out_xxx directly
* Bug fix - out_indices mapping from out_features
* Fix tests
* Dont accept output_loading_info for Timm models
* Set out_xxx and don't remap
* Use smaller checkpoint for test
* Don't remap timm indices - check out_indices based on stage names
* Skip test as it's n/a
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Cleaner imports / spelling is hard
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fix for ragged list
* unpin numba
* make style
* np.object -> object
* propagate changes to tokenizer as well
* np.long -> "long"
* revert tokenization changes
* check with tokenization changes
* list/tuple logic
* catch numpy
* catch else case
* clean up
* up
* better check
* trigger ci
* Empty commit to trigger CI
* mixed precision support via accelerate
* fix issues
* fix for the sharded ddp case
* fix flax and tf failing tests
* `refactor the place to create `Accelerator` object
* move ddp prep to accelerate
* fix 😅
* resolving comments
* move fsdp handling to accelerate
* fixex
* fix saving
* shift torch dynamo handling to accelerate
* shift deepspeed integration and save & load utils to accelerate
* fix accelerate launcher support
* oops
* fix 🐛
* save ckpt fix
* Trigger CI
* nasty 🐛😅
* as deepspeed needs grad_acc fixes, transfer grad_acc to accelerate
* make tests happy
* quality ✨
* loss tracked needs to account for grad_acc
* fixing the deepspeed tests
* quality ✨
* 😅😅😅
* tests 😡
* quality ✨
* Trigger CI
* resolve comments and fix the issue with the previous merge from branch
* Trigger CI
* accelerate took over deepspeed integration
---------
Co-authored-by: Stas Bekman <stas@stason.org>
* Add tf code for efficientformer
* Fix return dict bug - return last hidden state after last stage
* Fix corresponding return dict bug
* Override test tol
* Change default values of training to False
* Set training to default False X3
* Rm axis from ln
* Set init in dense projection
* Rm debug stuff
* Make style; all tests pass.
* Modify year to 2023
* Fix attention biases codes
* Update the shape list logic
* Add a batch norm eps config
* Remove extract comments in test files
* Add conditional attn and hidden states return for serving output
* Change channel dim checking logic
* Add exception for withteacher model in training mode
* Revert layer count for now
* Add layer count for conditional layer naming
* Transpose for conv happens only in main layer
* Make tests smaller
* Make style
* Update doc
* Rm from_pt
* Change to actual expect image class label
* Remove stray print in tests
* Update image processor test
* Remove the old serving output logic
* Make style
* Make style
* Complete test
* Let's try autodetecting serving sigs
* Don't clobber existing sigs
* Change shapes for multiplechoice models
* Make default dummy inputs smarter too
* Fix missing f-string
* Let's YOLO a serving output too
* Read __class__.__name__ properly
* Don't just pass naked lists in there and expect it to be okay
* Code cleanup
* Update default serving sig
* Clearer error messages
* Further updates to the default serving output
* make fixup
* Update the serving output a bit more
* Cleanups and renames, raise errors appropriately when we can't infer inputs
* More renames
* we're building in a functional context again, yolo
* import DUMMY_INPUTS from the right place
* import DUMMY_INPUTS from the right place
* Support cross-attention in the dummies
* Support cross-attention in the dummies
* Complete removal of dummy/serving overrides in BERT
* Complete removal of dummy/serving overrides in RoBERTa
* Obliterate lots and lots of serving sig and dummy overrides
* merge type hint changes
* Fix for token_type_ids with vocab_size 1
* Add missing property decorator
* Fix T5 and hopefully some models that take conv inputs
* More signature pruning
* Fix T5's signature
* Fix Wav2Vec2 signature
* Fix LongformerForMultipleChoice input signature
* Fix BLIP and LED
* Better default serving output error handling
* Fix BART dummies
* Fix dummies for cross-attention, esp encoder-decoder models
* Fix visionencoderdecoder signature
* Fix BLIP serving output
* Small tweak to BART dummies
* Cleanup the ugly parameter inspection line that I used in a few places
* committed a breakpoint again
* Move the text_dims check
* Remove blip_text serving_output
* Add decoder_input_ids to the default input sig
* Remove all the manual overrides for encoder-decoder model signatures
* Tweak longformer/led input sigs
* Tweak default serving output
* output.keys() -> output
* make fixup
* 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
* Added lion and paged optimizers and made original tests pass.
* Added tests for paged and lion optimizers.
* Added and fixed optimizer tests.
* Style and quality checks.
---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
* Added lion and paged optimizers and made original tests pass.
* Added tests for paged and lion optimizers.
* Added and fixed optimizer tests.
* Style and quality checks.
* Initial draft. Some tests fail.
* Fixed dtype bug.
* Fixed bug caused by torch_dtype='auto'.
* All test green for 8-bit and 4-bit layers.
* Added fix for fp32 layer norms and bf16 compute in LLaMA.
* Initial draft. Some tests fail.
* Fixed dtype bug.
* Fixed bug caused by torch_dtype='auto'.
* All test green for 8-bit and 4-bit layers.
* Added lion and paged optimizers and made original tests pass.
* Added tests for paged and lion optimizers.
* Added and fixed optimizer tests.
* Style and quality checks.
* Fixing issues for PR #23479.
* Added fix for fp32 layer norms and bf16 compute in LLaMA.
* Reverted variable name change.
* Initial draft. Some tests fail.
* Fixed dtype bug.
* Fixed bug caused by torch_dtype='auto'.
* All test green for 8-bit and 4-bit layers.
* Added lion and paged optimizers and made original tests pass.
* Added tests for paged and lion optimizers.
* Added and fixed optimizer tests.
* Style and quality checks.
* Added missing tests.
* Fixup changes.
* Added fixup changes.
* Missed some variables to rename.
* revert trainer tests
* revert test trainer
* another revert
* fix tests and safety checkers
* protect import
* simplify a bit
* Update src/transformers/trainer.py
* few fixes
* add warning
* replace with `load_in_kbit = load_in_4bit or load_in_8bit`
* fix test
* fix tests
* this time fix tests
* safety checker
* add docs
* revert torch_dtype
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* multiple fixes
* update docs
* version checks and multiple fixes
* replace `is_loaded_in_kbit`
* replace `load_in_kbit`
* change methods names
* better checks
* oops
* oops
* address final comments
---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* First commit
* Add auto-translation with GPT-4
* make fixup
* Add a functional layernorm for TF
* Add all the auxiliary imports etc.
* Add the extra processor and tests
* rebase to main
* Add all the needed fixes to the GPT code
* make fixup
* Make convolutions channels-last so they run on CPU
* make fixup
* Fix final issues
* Fix other models affected by test change
* Clarify comment on the sparse_prompt_embeddings check
* Refactor functional_layernorm, use shape_list in place of .shape in some places
* Remove deprecated torch-alike code
* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Refactor processor with common methods and separated private methods
* make fixup
* Quietly delete the file that didn't do anything (sorry Sylvain)
* Refactor the processor tests into one file
* make fixup
* Clean up some unnecessary indirection
* Fix TF mask postprocessing
* Add more processor equivalence tests
* Refactor generate_crop_boxes to use framework-neutral np code
* Make the serving output correctly conditional
* Fix error message line length
* Use dict keys rather than indices internally in both TF and PT SAM call/forward
* Return dicts internally in the call/forward methods
* Revert changes to common tests and just override check_pt_tf_outputs
* Revert changes to other model tests
* Clarify comments for functional layernorm
* Add missing transpose from PT code
* Removed unused copied from in PT code
* Remove overrides for tests that don't exist in TF
* Fix transpose and update tests for PT and TF to check pred_masks
* Add training flag
* Update tests to use TF checkpoints
* Update index.mdx
* Add missing cross-test decorator
* Remove optional extra asterisks
* Revert return_dict changes in PT code
* Update src/transformers/models/sam/modeling_tf_sam.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Remove None return annotations on init methods
* Update tests/models/sam/test_processor_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fix input_boxes shapes
* make fixup
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* initial working additions
* clean and rename, add cond stripping initial prompt to decode
* cleanup, edit create_initial_prompt_ids, add tests
* repo consistency, flip order of conditional
* fix error, move the processor fn to the tokenizer
* repo consistency, update test ids to corresponding tokenizer
* use convert_tokens_to_ids not get_vocab...
* use actual conditional in generate
* make sytle
* initial address comments
* initial working add new params to pipeline
* first draft of sequential generation for condition_on_previous_text
* add/update tests, make compatible with timestamps
* make compatible with diff. input kwargs and max length
* add None check
* add temperature check
* flip temp check operand
* refocusing to prev pr scope
* remove the params too
* make style
* edits, move max length incorporating prompt to whisper
* address comments
* remove asr pipeline prompt decoding, fix indexing
* address comments (more tests, validate prompt)
* un-comment out tests (from debug)
* remove old comment
* address comments
* fix typo
* remove timestamp token from test
* make style
* cleanup
* copy method to fast tokenizer, set max_new_tokens for test
* prompt_ids type just pt
* address Amy's comments
* make style
