GitLab

Log the right train_batch_size if using auto_find_batch_size and also log the adjusted value seperately. (#23800)

* Log right bs

* Log

* Diff message

* Fix no such file or directory error

* Address comment

* Fix formatting issue

Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

class_weights tensor should follow model's device

small doc nit

fix nllb moe accelerate issue

Bump tornado in /examples/research_projects/visual_bert

Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.0.4 to 6.3.2.
- [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst)
- [Commits](https://github.com/tornadoweb/tornado/compare/v6.0.4...v6.3.2

)

---
updated-dependencies:
- dependency-name: tornado
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.0.4 to 6.3.2.
- [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst)
- [Commits](https://github.com/tornadoweb/tornado/compare/v6.0.4...v6.3.2

)

---
updated-dependencies:
- dependency-name: tornado
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Fix is_ninja_available()

search ninja using subprocess instead of importlib.

* Fix style

* Fix doc

* Fix style

* remove unused parameters

* remove unused parameters in config

* Revamp test selection for the example tests

* Rename old XLA test and fake modif in run_glue

* Fixes

* Fake Trainer modif

* Remove fake modifs

Fix command in modeling_utils.py

Remove some more serving methods that (I think?) turned up while this PR was open

* Enable prompts on the Hub

* Update src/transformers/tools/prompts.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Address review comments

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Check for use_sagemaker_dp

* Add a check for is_sagemaker_mp when setting _n_gpu again. Should be last broken thing

* Try explicit check?

* Quality

Fix the regex in `get_imports` to support multiline try blocks and excepts with specific exception types (#23725)

* fix and test get_imports for multiline try blocks, and excepts with specific errors

* fixup

* add some more tests

* add license

* 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

move text_prompt_ids trimming to top

fix: delete duplicate sentence

* Extremely small change to TF SAM dummies to reduce memory usage on build

* remove debug breakpoint

* Debug print statement to track array sizes

* More debug shape printing

* More debug shape printing

* Now remove the debug shape printing

* make fixup

* make fixup

Minor docs fixes

* 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

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

fix: use bool instead of uint8/byte in Deberta/DebertaV2/SEW-D to make it compatible with TensorRT (#23683)

* Use bool instead of uint8/byte in DebertaV2 to make it compatible with TensorRT

TensorRT cannot accept onnx graph with uint8/byte intermediate tensors. This PR uses bool tensors instead of unit8/byte tensors to make the exported onnx file can work with TensorRT.

* fix: use bool instead of uint8/byte in Deberta and SEW-D

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Co-authored-by: Yuxian Qiu <yuxianq@nvidia.com>

* doc refocused on using optimum, tflite

* minor updates to fix checks

* Apply suggestions from code review
Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>

* TFLite to separate page, added links

* Removed the onnx list builder

* make style

* Update docs/source/en/serialization.mdx
Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>

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Co-authored-by: regisss <15324346+regisss@users.noreply.github.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.

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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

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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>

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Fix some docs what layerdrop does

* Update src/transformers/models/data2vec/configuration_data2vec_audio.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix more docs

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Ref: https://github.com/huggingface/peft/issues/394
    Loading a quantized checkpoint into non-quantized Linear8bitLt is not supported.
    call module.cuda() before module.load_state_dict()

fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix is_batched code to allow 2-D numpy arrays for audio

* Tests

* Fix typo

* Incorporate comments from PR #23223

fix blip doctest

* New TF version compatibility fixes

* Remove dummy print statement, move expand_1d

* Make a proper framework inference function

* Make a proper framework inference function

* ValueError -> TypeError

* add a dummy pipeline test

* change test name

fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>