security

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

* add import guards

* nit

Fix device in tests

* fix audio classification pipeline fp16 test on cuda

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* add comments

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* Update tests/pipelines/test_pipelines_audio_classification.py

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

add autoawq

Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* tests: revert change of torch_require_multi_gpu to be device agnostic

The 11c27dd3 modified `torch_require_multi_gpu()` to be device agnostic
instead of being CUDA specific. This broke some tests which are rightfully
CUDA specific, such as:

* `tests/trainer/test_trainer_distributed.py::TestTrainerDistributed`

In the current Transformers tests architecture `require_torch_multi_accelerator()`
should be used to mark multi-GPU tests agnostic to device.

This change addresses the issue introduced by 11c27dd3 and reverts
modification of `torch_require_multi_gpu()`.

Fixes: 11c27dd3

 ("Enable BNB multi-backend support (#31098)")
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>

* fix bug: modification of frozen set

---------

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Co-authored-by: Titus von Koeller <9048635+Titus-von-Koeller@users.noreply.github.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

fixed the batch_size error, all tests are passing

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update generation_whisper.py

Added handling for <2 length of suppress_tokens for whisper

* Updated None check for suppress_tokens to avoid ambiguity

---------

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* fix indentation issues + modular without magic keyword

* style

* Update doc.py

* style

* Fix all decorators indentation

* all models

* style

* style

* Update doc.py

* fix

* general fix

* style

Update _get_eval_sampler to reflect Trainer.tokenizer is deprecation  self.tokenizer -> self.processing_class (#36315)

* fix warning self.tokenizer -> self.processing_class

* formating change

* enable torchao quantization on CPU

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix int4

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* enable CPU torchao tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix cuda tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix cpu tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix style

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix cuda tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix torchao available

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix torchao available

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix torchao config cannot convert to json

* fix docs

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* rm to_dict to rebase

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* limited torchao version for CPU

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix skip

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* Update src/transformers/testing_utils.py

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* fix cpu test

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

fix

* Add check

* just check for function

* Update examples

* caching allocator warmup

* Update modeling_utils.py

* reuse expanded map

* style

Fixed a potential bug in modeling_llava_onevision.py

notify new model

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

* hoist keys

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

* remove hoist

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

---------

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

pip pytorch index should match docker base image

* Add autoquant support for torchao quantizer

Summary:
att, also verified that autoquantized model can be saved and loaded:

save: https://gist.github.com/jerryzh168/01d367aaf44dbbbfd4068a4a10a00061
load: https://gist.github.com/jerryzh168/d5c6c401b2abdf18e0b6771341f1525c

Test Plan:
tested locally with above script
model uploaded to https://huggingface.co/jerryzh168/llama3-8b-autoquant

Reviewers:

Subscribers:

Tasks:

Tags:

* add test

* ruff fix

* ruff reformat

* add docs and min_sqnr support

* format

* format

* fix test

* update doc

* format

* remove disable_compile

* format

* Disable warnings for stacked compressors
* Introduce two new hooks in HfQuantizer lifecycle
to allow updates to missing and unexpected keys
* Update missing and unexpected keys
for stacked compressors
* Add tests
* Fix: run_compressed cases
* Fix: uncompressed cases

* Rename compressed_tensor folder to compressed_tensors
Move RunCompressedTest to the same file
Update tests to unittest

* fix failed test

* fix device

* fix more device cases

* add more cases

* fix empty cache

* Update test_4bit.py

---------

Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Fix potential regex catastrophic backtracking in NougatTokenizerFast

The original regex pattern in tokenization_nougat_fast.py was vulnerable to
catastrophic backtracking due to greedy quantifiers and nested alternations.
This commit replaces it with a more efficient pattern that:

1. Uses explicit character classes instead of dot (.)
2. Handles whitespace more precisely
3. Avoids unnecessary backtracking
4. Supports both lowercase and uppercase roman numerals
5. Maintains the same functionality while being more robust

* Try another regex

* Trying deepseek's answer

* Start with a simplification

* Another simplification

* Just rewrite the whole function myself

* Fix gptneox and gptsan

* Simplify the regex even further

* Tighten up the price regex a little

* Add possessive version of the regex

* Fix regex

* Much cleaner regexes

---------

Co-authored-by: openhands <openhands@all-hands.dev>

* Uses Collection instead of Sequence in transformers.image_transforms.normalize

* Uses collections.abc.Collection in lieu of deprecated typing one

* make device-agnostic

* name change

* Docs

* Inits

* Auto classes

* Add siglip base

* Add base tests

* Fix Siglip V1 for fix res version

* Add image processor

* Update conversion

* Experimenting with vectorized embeddings

* Fixup

* Add modular Siglip2Processor

* Add modular configuration

* Rename num patches

* Correct image and text features merging

* Working conversion script

* Refactoring conversion script

* Remove unused code in conversion script

* Shorten dict a bit

* Refactoring conversion

* Done conversion refactoring

* Fixup

* Modular siglip2

* Make model exportable and compilable without graph breaks

* Remove position_ids from image_processor

* REmove position ids from modeling file

* Update modular

* Type hint

* Fixup

* Set defaults to processor

* Add integration test

* Revert spatial shapes back to tensor

* Change order

* Fix most of the tests

* Fix docstring

* Remove interpolate_pos_encoding arg (not needed)

* Update docs

* Standardize processing

* Fix attention_mask in vision head

* Siglip v1: remove double transpose in FA2

* Update modular file

* Update FA2 test

* Update expected logits

* Fix interpolation for siglip2 image processor

* Skip init test

* Skip dispatch on flash test

* Fix modeling tests

* Fixup

* Add dummy objects

* Fix some docstrings

* Add siglip2 in index.md

* Fix consistency

* Add docs

* Remove size and data format

* Add image processor tests

* Fix

* Add fast image processor

* Fix style

* Fix

* Docs

* Set lowercase for tokenizer

* Adjust head size for Siglip v1

* Update siglip2 for consistency with siglip1

* Update siglip2 conversion

* Update pipeline

* Update checkpoints in tests

* Update checkpoint name

* Fix pooling for image classification model

* Fix FA2 test

* Update processor

* Fix check repo

* Update docs

* Fix typos

* Fix docstring for fast image processor

* Add siglip2 to FA2 docs

* Fix fast ip tests

* Fix constitency

* Fix tokenizer class for siglip v1

* Fix missing header

* Refactor scaling for clip, siglip, siglip2

* Remove unused imports

* Make fast IP default for siglip2

* Update docs

* Update checkpoints

* Update modular

* Update paper link

* Fixup

* Fix name in toctree

* Fix test

* squash

* style

* add smolvlm to toctree

* add requirements

* dev-ci

* no docker changes

* dev-ci

* update torch-light.dockerfile

* derp

* dev-ci

* fix: prevent second save in the end of training

* fix: prevent second save in the end of training

* test: added test for no duplicate save on epoch save strategy

* fix: removed TrainerControl

* chore: style formatting

---------

Co-authored-by: JaktensTid <jaktenstid1@gmail.com>

Fix typo

* smolvlm init

* updates

* fixing bugs

* minimal run, no checks

* minimal run, no checks

* passing first check + adding url support

* updating video dataloading logic

* fixing image logic

* trying modular, but fails

* modular is working, changing processor to match PR comments and general transformers logic

* fixing kwargs

* offloading video loading logic to  image_util

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* fixing circleci code formatting errors

* update

* add idefics3-based tests

* add keyword to all

* add PreTrainedModel

* updateing video loading logic

* working inference

* updates for PR comments

* updates for PR comments

* moving SmolVLMPretrainedModel higher to fix import error

* CI test pass

* CI test pass

* removing lambda

* CI test pass

* CI test pass

* CI test pass

* CI test pass

* CI test pass

* CI test pass

* processor tests

* add example in docs

* typo

* fix copies

* skip compile tests - sdpa for VisionTransformer

* fix init

* raise import error for num2words

* update doc for FA2

* more doc fix

* CI

* updates for PR comments

* Update docs/source/en/model_doc/smolvlm.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/model_doc/smolvlm.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/model_doc/smolvlm.md

Co-authored-by: Joshua Lochner <admin@xenova.com>

* Update docs/source/en/model_doc/smolvlm.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/model_doc/smolvlm.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fixing processor -- tokenizer not defined properly, (gpt2 tokenizer), and does not have the attributes of fake image token, etc

* adding smolvlm to VQA models

* removing vqa auto class

* Update src/transformers/models/smolvlm/processing_smolvlm.py

Co-authored-by: Joshua Lochner <admin@xenova.com>

* removing smolvlmvisiontransformer from index.md

* my bad, video processing had typos

* fixing docs

* renaming params in SmolVLMModel.inputs_merger

* removing un-needed dtype/device in model forward

* ruff for CI

* update docs

* Update docs/source/en/model_doc/smolvlm.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* return cache position

* return cache position

* return cache also in modular

* needed to run modular again

* fix training tests

* push vectorized inputs merger

* format

* format

* reduce number of mappings

* addressing PR comments

* happy CI, happy me :)

* skip non-nested images

* adjust integration test for smaller GPUs

* format

* fix kwargs in chat template apply

* skip this for now

---------

Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: Pablo <pablo.montalvo.leroux@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Joshua Lochner <admin@xenova.com>

fix

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

* fix

* fix

---------

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

simply make cache traceable