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Generation: deprecate PreTrainedModel inheriting from GenerationMixin #33203

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merged 15 commits into from
Sep 23, 2024

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gante
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@gante gante commented Aug 29, 2024

What does this PR do?

Step 2 of #32685 - Deprecates the GenerationMixin inheritance from PreTrainedModel. Instead, models classes with generative capabilities are expected to inherit GenerationMixin directly.

This PR:

Why?

Currently, we have a circular logic dependency between PreTrainedModel and GenerationMixin:

  • PreTrainedModel 👈 GenerationMixin: PreTrainedModel has a can_generate() method, which depends on methods that exist in GenerationMixin. Depending on the value of can_generate(), it may hold a GenerationConfig object.
  • GenerationMixin 👈 PreTrainedModel: GenerationMixin needed to inspect the type of the model instance, to throw informative exceptions at the user. This was needed because ALL our models could call generate, but most of them didn't support it.

This PR sets the deprecation cycle to break this circular dependency:

  1. GenerationMixin becomes a stand-alone class with no dependencies on PreTrainedModel. It is now a proper mixin: it may even be used with other model base classes, if users desire to do so.
  2. PreTrainedModel doesn't inherit GenerationMixin. This means that non-generative models will become less bloated 🤏 💛

What else can we improve as a result of this change?

  1. [added in this PR] can_generate() is no longer dependent on overwrites: if a model is a subclass of GenerationMixin then it can generate
  2. no need to validate the model class in generate -- all GenerationMixin subclasses can call generate
  3. Because of 1., all the changes planned in tracker: move prepare_inputs_for_generation into the generation mixin 🧹  #32685 become much simpler to implement (can_generate() no longer depends on prepare_inputs_for_generation -> easier to make structural changes there) 🤗
  4. Perhaps in the future, we can move the GenerationConfig instance to GenerationMixin, so that non-generative models don't hold a generation_config attribute.

🚨🚨 caveats 🚨🚨

After removing the deprecated code:
✅ Loading old hub models with custom code, using our auto classes, and calling generate
❌ Loading old hub models with custom code, using the custom model code directly, and calling generate. An informative exception will be thrown, suggesting to use our auto classes and sharing instructions on how to solve the problem if that is not possible 🤗

@gante gante marked this pull request as ready for review August 29, 2024 19:04
MODEL_FOR_VISION_2_SEQ_MAPPING,
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
terminations_with_generation_support = [
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Note: This function was touched to avoid a circular import (the from ..models.auto imports)

# BC: Detects whether `prepare_inputs_for_generation` has been overwritten in the model. Prior to v4.45, this
# was how we detected whether a model could generate.
if "GenerationMixin" not in str(cls.prepare_inputs_for_generation):
logger.warning_once(
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This warning should only appear in the case that is not BC after removing the GenerationMixin inheritance in PreTrainedModel. See caveats section of the PR header.

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gante commented Aug 29, 2024

I think the test fetched is failing because I've touched too many files 🙃

@HuggingFaceDocBuilderDev

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

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Thanks for the PR @gante! I think @ArthurZucker is better suited than I am to review this PR given the changes they do to the modeling code; will defer to him for the initial review

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ydshieh commented Aug 30, 2024

@gante you can probably try [test_all] commit message and see if the fetcher would survive

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gante commented Sep 2, 2024

@ydshieh the new fetcher doesn't complain 🙌

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Cool! Thanks for this chore update!

if "GenerationMixin" in str(cls.__bases__):
return True
# Model class overwrites `generate` -> can generate
if str(cls.__class__.__name__) in str(cls.generate):
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if it does not inherit from generationMixin should we rais an error?

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@gante gante Sep 6, 2024

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Not quite, we have the time series models that overwrite generate (and, prior to this change, can_generate() returned True for them)

@gante gante requested a review from ArthurZucker September 6, 2024 16:26
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gante commented Sep 20, 2024

(@ArthurZucker ping :) Merging this will unblock the migration of prepare_inputs_for_generate to GenerationMixin)

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Sorry for the delay, thanks for fixing!

@gante gante merged commit e15687f into huggingface:main Sep 23, 2024
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@gante gante deleted the isolated_mixin branch September 23, 2024 17:28
avishaiElmakies pushed a commit to avishaiElmakies/transformers that referenced this pull request Sep 25, 2024
ArthurZucker added a commit that referenced this pull request Oct 10, 2024
* add sdpa to OPT

* chore: remove redundant whitespace in OPTDecoder class

* fixup

* bug fix

* add sdpa and attention generate test

* fixup

* Refactor OPTAttention forward method for improved readability and maintainability

* undo refactor for _shape and key,val states

* add OPT to doc, fixup didn't find it for some reason

* change order

* change default attn_implemntation in testing to eager

* [run-slow] opt

* change test_eager_matches_sdpa_generate to the one llama

* Update default attention implementation in testing common

* [run-slow] opt

* remove uneeded print

* [run-slow] opt

* refactor model testers to have attn_implementation="eager"

* [run-slow] opt

* convert test_eager_matches_sdpa_generate to opt-350M

* bug fix when creating mask for opt

* [run-slow] opt

* if layer head mask default to eager

* if head mask is not none fall to eager

* [run-slow] opt

* Update src/transformers/models/opt/modeling_opt.py

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

* Clean up Unpack imports (#33631)

clean up Unpack imports

* Fix DPT /Dinov2 sdpa regression on main (#33660)

* fallback to eager if output attentions.

* fix copies

* handle dependency errors in check_imports (#33622)

* handle dependency errors in check_imports

* change log level to warning

* add back self.max_position_embeddings = config.max_position_embeddings (#33550)

* add back self.max_position_embeddings = config.max_position_embeddings

* fix-copies

* Fix Llava conversion for LlavaQwen2ForCausalLM with Clip vision tower (#33613)

fix llavaqwen2 model conversion

* Uniformize kwargs for Udop processor and update docs (#33628)

* Add optional kwargs and uniformize udop

* cleanup Unpack

* nit Udop

* Generation: deprecate `PreTrainedModel` inheriting from `GenerationMixin`  (#33203)

* Enable BNB multi-backend support (#31098)

* enable cpu bnb path

* fix style

* fix code style

* fix 4 bit path

* Update src/transformers/utils/import_utils.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* add multi backend refactor tests

* fix style

* tweak 4bit quantizer + fix corresponding tests

* tweak 8bit quantizer + *try* fixing corresponding tests

* fix dequant bnb 8bit

* account for Intel CPU in variability of expected outputs

* enable cpu and xpu device map

* further tweaks to account for Intel CPU

* fix autocast to work with both cpu + cuda

* fix comments

* fix comments

* switch to testing_utils.torch_device

* allow for xpu in multi-gpu tests

* fix tests 4bit for CPU NF4

* fix bug with is_torch_xpu_available needing to be called as func

* avoid issue where test reports attr err due to other failure

* fix formatting

* fix typo from resolving of merge conflict

* polish based on last PR review

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

* fix CI

* Update src/transformers/integrations/integration_utils.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/integrations/integration_utils.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix error log

* fix error msg

* add \n in error log

* make quality

* rm bnb cuda restriction in doc

* cpu model don't need dispatch

* fix doc

* fix style

* check cuda avaliable in testing

* fix tests

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

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

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

Co-authored-by: Aarni Koskela <akx@iki.fi>

* Update tests/quantization/bnb/test_4bit.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* Update tests/quantization/bnb/test_4bit.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* fix doc

* fix check multibackends

* fix import sort

* remove check torch in bnb

* docs: update bitsandbytes references with multi-backend info

* docs: fix small mistakes in bnb paragraph

* run formatting

* reveret bnb check

* move bnb multi-backend check to import_utils

* Update src/transformers/utils/import_utils.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* fix bnb check

* minor fix for bnb

* check lib first

* fix code style

* Revert "run formatting"

This reverts commit ac108c6.

* fix format

* give warning when bnb version is low and no cuda found]

* fix device assignment check to be multi-device capable

* address akx feedback on get_avlbl_dev fn

* revert partially, as we don't want the function that public, as docs would be too much (enforced)

---------

Co-authored-by: Aarni Koskela <akx@iki.fi>
Co-authored-by: Titus von Koeller <9048635+Titus-von-Koeller@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix error string after refactoring into get_chat_template (#33652)

* Fix error string after refactoring into get_chat_template

* Take suggestion from CR

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

---------

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* uniformize git processor (#33668)

* uniformize git processor

* update doctring

* Modular `transformers`: modularity and inheritance for new model additions (#33248)

* update exampel

* update

* push the converted diff files for testing and ci

* correct one example

* fix class attributes and docstring

* nits

* oups

* fixed config!

* update

* nitd

* class attributes are not matched against the other, this is missing

* fixed overwriting self.xxx now onto the attributes I think

* partial fix, now order with docstring

* fix docstring order?

* more fixes

* update

* fix missing docstrings!

* examples don't all work yet

* fixup

* nit

* updated

* hick

* update

* delete

* update

* update

* update

* fix

* all default

* no local import

* fix more diff

* some fix related to "safe imports"

* push fixed

* add helper!

* style

* add a check

* all by default

* add the

* update

* FINALLY!

* nit

* fix config dependencies

* man that is it

* fix fix

* update diffs

* fix the last issue

* re-default to all

* alll the fixes

* nice

* fix properties vs setter

* fixup

* updates

* update dependencies

* make sure to install what needs to be installed

* fixup

* quick fix for now

* fix!

* fixup

* update

* update

* updates

* whitespaces

* nit

* fix

* simplify everything, and make it file agnostic (should work for image processors)

* style

* finish fixing all import issues

* fixup

* empty modeling should not be written!

* Add logic to find who depends on what

* update

* cleanup

* update

* update gemma to support positions

* some small nits

* this is the correct docstring for gemma2

* fix merging of docstrings

* update

* fixup

* update

* take doc into account

* styling

* update

* fix hidden activation

* more fixes

* final fixes!

* fixup

* fixup instruct  blip video

* update

* fix bugs

* align gemma2 with the rest as well

* updats

* revert

* update

* more reversiom

* grind

* more

* arf

* update

* order will matter

* finish del stuff

* update

* rename to modular

* fixup

* nits

* update makefile

* fixup

* update order of the checks!

* fix

* fix docstring that has a call inside

* fiix conversion check

* style

* add some initial documentation

* update

* update doc

* some fixup

* updates

* yups

* Mostly todo gimme a minut

* update

* fixup

* revert some stuff

* Review docs for the modular transformers (#33472)

Docs

* good update

* fixup

* mmm current updates lead to this code

* okay, this fixes it

* cool

* fixes

* update

* nit

* updates

* nits

* fix doc

* update

* revert bad changes

* update

* updates

* proper update

* update

* update?

* up

* update

* cool

* nits

* nits

* bon bon

* fix

* ?

* minimise changes

* update

* update

* update

* updates?

* fixed gemma2

* kind of a hack

* nits

* update

* remove `diffs` in favor of `modular`

* fix make fix copies

---------

Co-authored-by: Lysandre Debut <hi@lysand.re>

* Fix CIs post merging modular transformers (#33681)

update

* Fixed docstring for cohere model regarding unavailability of prune_he… (#33253)

* Fixed docstring for cohere model regarding unavailability of prune_head() methods

The docstring mentions that cohere model supports prune_heads() methods. I have fixed the docstring by explicitly mentioning that it doesn't support that functionality.

* Update src/transformers/models/cohere/modeling_cohere.py

---------

Co-authored-by: Lysandre Debut <hi@lysand.re>

* Generation tests: update imagegpt input name, remove unused functions (#33663)

* Improve Error Messaging for Flash Attention 2 on CPU (#33655)

Update flash-attn error message on CPU

Rebased to latest branch

* Gemma2: fix config initialization (`cache_implementation`) (#33684)

* Fix ByteLevel alphabet missing when Sequence pretokenizer is used (#33556)

* Fix ByteLevel alphabet missing when Sequence pretokenizer is used

* Fixed formatting with `ruff`.

* Uniformize kwargs for image-text-to-text processors (#32544)

* uniformize FUYU processor kwargs

* Uniformize instructblip processor kwargs

* Fix processor kwargs and tests Fuyu, InstructBlip, Kosmos2

* Uniformize llava_next processor

* Fix save_load test for processor with chat_template only as extra init args

* Fix import Unpack

* Fix Fuyu Processor import

* Fix FuyuProcessor import

* Fix FuyuProcessor

* Add defaults for specific kwargs kosmos2

* Fix Udop to return BatchFeature instead of BatchEncoding and uniformize kwargs

* Add tests processor Udop

* remove Copied from in processing Udop as change of input orders caused by BatchEncoding -> BatchFeature

* Fix overwrite tests kwargs processors

* Add warnings and BC for changes in processor inputs order, change docs, add BC for text_pair as arg for Udop

* Fix processing test fuyu

* remove unnecessary pad_token check in instructblip ProcessorTest

* Fix BC tests and cleanup

* FIx imports fuyu

* Uniformize Pix2Struct

* Fix wrong name for FuyuProcessorKwargs

* Fix slow tests reversed inputs align fuyu llava-next, change udop warning

* Fix wrong logging import udop

* Add check images text input order

* Fix copies

* change text pair handling when positional arg

* rebase on main, fix imports in test_processing_common

* remove optional args and udop uniformization from this PR

* fix failing tests

* remove unnecessary test, fix processing utils and test processing common

* cleanup Unpack

* cleanup

* fix conflict grounding dino

* 🚨🚨 Setting default behavior of assisted decoding (#33657)

* tests: fix pytorch tensor placement errors (#33485)

This commit fixes the following errors:
* Fix "expected all tensors to be on the same device" error
* Fix "can't convert device type tensor to numpy"

According to pytorch documentation torch.Tensor.numpy(force=False)
performs conversion only if tensor is on CPU (plus few other restrictions)
which is not the case. For our case we need force=True since we just
need a data and don't care about tensors coherency.

Fixes: #33517
See: https://pytorch.org/docs/2.4/generated/torch.Tensor.numpy.html

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>

* bump tokenizers, fix added tokens fast (#32535)

* update based on tokenizers release

* update

* nits

* update

* revert re addition

* don't break that yet

* fmt

* revert unwanted

* update tokenizers version

* update dep table

* update

* update in conversion script as well

* some fix

* revert

* fully revert

* fix training

* remove set trace

* fixup

* update

* update

* [Pixtral] Improve docs, rename model (#33491)

* Improve docs, rename model

* Fix style

* Update repo id

* fix code quality after merge

* HFQuantizer implementation for compressed-tensors library (#31704)

* Add compressed-tensors HFQuantizer implementation

* flag serializable as False

* run

* revive lines deleted by ruff

* fixes to load+save from sparseml, edit config to quantization_config, and load back

* address satrat comment

* compressed_tensors to compressed-tensors and revert back is_serializable

* rename quant_method from sparseml to compressed-tensors

* tests

* edit tests

* clean up tests

* make style

* cleanup

* cleanup

* add test skip for when compressed tensors is not installed

* remove pydantic import + style

* delay torch import in test

* initial docs

* update main init for compressed tensors config

* make fix-copies

* docstring

* remove fill_docstring

* Apply suggestions from code review

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

* review comments

* review comments

* comments - suppress warnings on state dict load, tests, fixes

* bug-fix - remove unnecessary call to apply quant lifecycle

* run_compressed compatability

* revert changes not needed for compression

* no longer need unexpected keys fn

* unexpected keys not needed either

* Apply suggestions from code review

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

* add to_diff_dict

* update docs and expand testing

* Update _toctree.yml with compressed-tensors

* Update src/transformers/utils/quantization_config.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* update doc

* add note about saving a loaded model

---------

Co-authored-by: George Ohashi <george@neuralmagic.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Sara Adkins <sara@neuralmagic.com>
Co-authored-by: Sara Adkins <sara.adkins65@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Dipika Sikka <ds3822@columbia.edu>
Co-authored-by: Dipika <dipikasikka1@gmail.com>

* update model card for opt

* add batch size to inference table

* [slow-run] opt

* [run-slow] opt

---------

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Co-authored-by: Avishai Elmakies <avishai.elma@cs.huji.ac.il>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
Co-authored-by: chengchengpei <5881383+chengchengpei@users.noreply.github.com>
Co-authored-by: Isotr0py <2037008807@qq.com>
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Aarni Koskela <akx@iki.fi>
Co-authored-by: Titus von Koeller <9048635+Titus-von-Koeller@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Tibor Reiss <75096465+tibor-reiss@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>
Co-authored-by: Muhammad Naufil <m.naufil1@gmail.com>
Co-authored-by: sizhky <yyeshr@gmail.com>
Co-authored-by: Umar Butler <umar@umar.au>
Co-authored-by: Jonathan Mamou <jonathan.mamou@intel.com>
Co-authored-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com>
Co-authored-by: George Ohashi <george@neuralmagic.com>
Co-authored-by: Sara Adkins <sara@neuralmagic.com>
Co-authored-by: Sara Adkins <sara.adkins65@gmail.com>
Co-authored-by: Dipika Sikka <ds3822@columbia.edu>
Co-authored-by: Dipika <dipikasikka1@gmail.com>
BernardZach pushed a commit to BernardZach/transformers that referenced this pull request Dec 5, 2024
BernardZach pushed a commit to BernardZach/transformers that referenced this pull request Dec 5, 2024
* add sdpa to OPT

* chore: remove redundant whitespace in OPTDecoder class

* fixup

* bug fix

* add sdpa and attention generate test

* fixup

* Refactor OPTAttention forward method for improved readability and maintainability

* undo refactor for _shape and key,val states

* add OPT to doc, fixup didn't find it for some reason

* change order

* change default attn_implemntation in testing to eager

* [run-slow] opt

* change test_eager_matches_sdpa_generate to the one llama

* Update default attention implementation in testing common

* [run-slow] opt

* remove uneeded print

* [run-slow] opt

* refactor model testers to have attn_implementation="eager"

* [run-slow] opt

* convert test_eager_matches_sdpa_generate to opt-350M

* bug fix when creating mask for opt

* [run-slow] opt

* if layer head mask default to eager

* if head mask is not none fall to eager

* [run-slow] opt

* Update src/transformers/models/opt/modeling_opt.py

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

* Clean up Unpack imports (huggingface#33631)

clean up Unpack imports

* Fix DPT /Dinov2 sdpa regression on main (huggingface#33660)

* fallback to eager if output attentions.

* fix copies

* handle dependency errors in check_imports (huggingface#33622)

* handle dependency errors in check_imports

* change log level to warning

* add back self.max_position_embeddings = config.max_position_embeddings (huggingface#33550)

* add back self.max_position_embeddings = config.max_position_embeddings

* fix-copies

* Fix Llava conversion for LlavaQwen2ForCausalLM with Clip vision tower (huggingface#33613)

fix llavaqwen2 model conversion

* Uniformize kwargs for Udop processor and update docs (huggingface#33628)

* Add optional kwargs and uniformize udop

* cleanup Unpack

* nit Udop

* Generation: deprecate `PreTrainedModel` inheriting from `GenerationMixin`  (huggingface#33203)

* Enable BNB multi-backend support (huggingface#31098)

* enable cpu bnb path

* fix style

* fix code style

* fix 4 bit path

* Update src/transformers/utils/import_utils.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* add multi backend refactor tests

* fix style

* tweak 4bit quantizer + fix corresponding tests

* tweak 8bit quantizer + *try* fixing corresponding tests

* fix dequant bnb 8bit

* account for Intel CPU in variability of expected outputs

* enable cpu and xpu device map

* further tweaks to account for Intel CPU

* fix autocast to work with both cpu + cuda

* fix comments

* fix comments

* switch to testing_utils.torch_device

* allow for xpu in multi-gpu tests

* fix tests 4bit for CPU NF4

* fix bug with is_torch_xpu_available needing to be called as func

* avoid issue where test reports attr err due to other failure

* fix formatting

* fix typo from resolving of merge conflict

* polish based on last PR review

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

* fix CI

* Update src/transformers/integrations/integration_utils.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/integrations/integration_utils.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix error log

* fix error msg

* add \n in error log

* make quality

* rm bnb cuda restriction in doc

* cpu model don't need dispatch

* fix doc

* fix style

* check cuda avaliable in testing

* fix tests

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

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

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

Co-authored-by: Aarni Koskela <akx@iki.fi>

* Update tests/quantization/bnb/test_4bit.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* Update tests/quantization/bnb/test_4bit.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* fix doc

* fix check multibackends

* fix import sort

* remove check torch in bnb

* docs: update bitsandbytes references with multi-backend info

* docs: fix small mistakes in bnb paragraph

* run formatting

* reveret bnb check

* move bnb multi-backend check to import_utils

* Update src/transformers/utils/import_utils.py

Co-authored-by: Aarni Koskela <akx@iki.fi>

* fix bnb check

* minor fix for bnb

* check lib first

* fix code style

* Revert "run formatting"

This reverts commit ac108c6.

* fix format

* give warning when bnb version is low and no cuda found]

* fix device assignment check to be multi-device capable

* address akx feedback on get_avlbl_dev fn

* revert partially, as we don't want the function that public, as docs would be too much (enforced)

---------

Co-authored-by: Aarni Koskela <akx@iki.fi>
Co-authored-by: Titus von Koeller <9048635+Titus-von-Koeller@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix error string after refactoring into get_chat_template (huggingface#33652)

* Fix error string after refactoring into get_chat_template

* Take suggestion from CR

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

---------

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* uniformize git processor (huggingface#33668)

* uniformize git processor

* update doctring

* Modular `transformers`: modularity and inheritance for new model additions (huggingface#33248)

* update exampel

* update

* push the converted diff files for testing and ci

* correct one example

* fix class attributes and docstring

* nits

* oups

* fixed config!

* update

* nitd

* class attributes are not matched against the other, this is missing

* fixed overwriting self.xxx now onto the attributes I think

* partial fix, now order with docstring

* fix docstring order?

* more fixes

* update

* fix missing docstrings!

* examples don't all work yet

* fixup

* nit

* updated

* hick

* update

* delete

* update

* update

* update

* fix

* all default

* no local import

* fix more diff

* some fix related to "safe imports"

* push fixed

* add helper!

* style

* add a check

* all by default

* add the

* update

* FINALLY!

* nit

* fix config dependencies

* man that is it

* fix fix

* update diffs

* fix the last issue

* re-default to all

* alll the fixes

* nice

* fix properties vs setter

* fixup

* updates

* update dependencies

* make sure to install what needs to be installed

* fixup

* quick fix for now

* fix!

* fixup

* update

* update

* updates

* whitespaces

* nit

* fix

* simplify everything, and make it file agnostic (should work for image processors)

* style

* finish fixing all import issues

* fixup

* empty modeling should not be written!

* Add logic to find who depends on what

* update

* cleanup

* update

* update gemma to support positions

* some small nits

* this is the correct docstring for gemma2

* fix merging of docstrings

* update

* fixup

* update

* take doc into account

* styling

* update

* fix hidden activation

* more fixes

* final fixes!

* fixup

* fixup instruct  blip video

* update

* fix bugs

* align gemma2 with the rest as well

* updats

* revert

* update

* more reversiom

* grind

* more

* arf

* update

* order will matter

* finish del stuff

* update

* rename to modular

* fixup

* nits

* update makefile

* fixup

* update order of the checks!

* fix

* fix docstring that has a call inside

* fiix conversion check

* style

* add some initial documentation

* update

* update doc

* some fixup

* updates

* yups

* Mostly todo gimme a minut

* update

* fixup

* revert some stuff

* Review docs for the modular transformers (huggingface#33472)

Docs

* good update

* fixup

* mmm current updates lead to this code

* okay, this fixes it

* cool

* fixes

* update

* nit

* updates

* nits

* fix doc

* update

* revert bad changes

* update

* updates

* proper update

* update

* update?

* up

* update

* cool

* nits

* nits

* bon bon

* fix

* ?

* minimise changes

* update

* update

* update

* updates?

* fixed gemma2

* kind of a hack

* nits

* update

* remove `diffs` in favor of `modular`

* fix make fix copies

---------

Co-authored-by: Lysandre Debut <hi@lysand.re>

* Fix CIs post merging modular transformers (huggingface#33681)

update

* Fixed docstring for cohere model regarding unavailability of prune_he… (huggingface#33253)

* Fixed docstring for cohere model regarding unavailability of prune_head() methods

The docstring mentions that cohere model supports prune_heads() methods. I have fixed the docstring by explicitly mentioning that it doesn't support that functionality.

* Update src/transformers/models/cohere/modeling_cohere.py

---------

Co-authored-by: Lysandre Debut <hi@lysand.re>

* Generation tests: update imagegpt input name, remove unused functions (huggingface#33663)

* Improve Error Messaging for Flash Attention 2 on CPU (huggingface#33655)

Update flash-attn error message on CPU

Rebased to latest branch

* Gemma2: fix config initialization (`cache_implementation`) (huggingface#33684)

* Fix ByteLevel alphabet missing when Sequence pretokenizer is used (huggingface#33556)

* Fix ByteLevel alphabet missing when Sequence pretokenizer is used

* Fixed formatting with `ruff`.

* Uniformize kwargs for image-text-to-text processors (huggingface#32544)

* uniformize FUYU processor kwargs

* Uniformize instructblip processor kwargs

* Fix processor kwargs and tests Fuyu, InstructBlip, Kosmos2

* Uniformize llava_next processor

* Fix save_load test for processor with chat_template only as extra init args

* Fix import Unpack

* Fix Fuyu Processor import

* Fix FuyuProcessor import

* Fix FuyuProcessor

* Add defaults for specific kwargs kosmos2

* Fix Udop to return BatchFeature instead of BatchEncoding and uniformize kwargs

* Add tests processor Udop

* remove Copied from in processing Udop as change of input orders caused by BatchEncoding -> BatchFeature

* Fix overwrite tests kwargs processors

* Add warnings and BC for changes in processor inputs order, change docs, add BC for text_pair as arg for Udop

* Fix processing test fuyu

* remove unnecessary pad_token check in instructblip ProcessorTest

* Fix BC tests and cleanup

* FIx imports fuyu

* Uniformize Pix2Struct

* Fix wrong name for FuyuProcessorKwargs

* Fix slow tests reversed inputs align fuyu llava-next, change udop warning

* Fix wrong logging import udop

* Add check images text input order

* Fix copies

* change text pair handling when positional arg

* rebase on main, fix imports in test_processing_common

* remove optional args and udop uniformization from this PR

* fix failing tests

* remove unnecessary test, fix processing utils and test processing common

* cleanup Unpack

* cleanup

* fix conflict grounding dino

* 🚨🚨 Setting default behavior of assisted decoding (huggingface#33657)

* tests: fix pytorch tensor placement errors (huggingface#33485)

This commit fixes the following errors:
* Fix "expected all tensors to be on the same device" error
* Fix "can't convert device type tensor to numpy"

According to pytorch documentation torch.Tensor.numpy(force=False)
performs conversion only if tensor is on CPU (plus few other restrictions)
which is not the case. For our case we need force=True since we just
need a data and don't care about tensors coherency.

Fixes: huggingface#33517
See: https://pytorch.org/docs/2.4/generated/torch.Tensor.numpy.html

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>

* bump tokenizers, fix added tokens fast (huggingface#32535)

* update based on tokenizers release

* update

* nits

* update

* revert re addition

* don't break that yet

* fmt

* revert unwanted

* update tokenizers version

* update dep table

* update

* update in conversion script as well

* some fix

* revert

* fully revert

* fix training

* remove set trace

* fixup

* update

* update

* [Pixtral] Improve docs, rename model (huggingface#33491)

* Improve docs, rename model

* Fix style

* Update repo id

* fix code quality after merge

* HFQuantizer implementation for compressed-tensors library (huggingface#31704)

* Add compressed-tensors HFQuantizer implementation

* flag serializable as False

* run

* revive lines deleted by ruff

* fixes to load+save from sparseml, edit config to quantization_config, and load back

* address satrat comment

* compressed_tensors to compressed-tensors and revert back is_serializable

* rename quant_method from sparseml to compressed-tensors

* tests

* edit tests

* clean up tests

* make style

* cleanup

* cleanup

* add test skip for when compressed tensors is not installed

* remove pydantic import + style

* delay torch import in test

* initial docs

* update main init for compressed tensors config

* make fix-copies

* docstring

* remove fill_docstring

* Apply suggestions from code review

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

* review comments

* review comments

* comments - suppress warnings on state dict load, tests, fixes

* bug-fix - remove unnecessary call to apply quant lifecycle

* run_compressed compatability

* revert changes not needed for compression

* no longer need unexpected keys fn

* unexpected keys not needed either

* Apply suggestions from code review

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

* add to_diff_dict

* update docs and expand testing

* Update _toctree.yml with compressed-tensors

* Update src/transformers/utils/quantization_config.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* update doc

* add note about saving a loaded model

---------

Co-authored-by: George Ohashi <george@neuralmagic.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Sara Adkins <sara@neuralmagic.com>
Co-authored-by: Sara Adkins <sara.adkins65@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Dipika Sikka <ds3822@columbia.edu>
Co-authored-by: Dipika <dipikasikka1@gmail.com>

* update model card for opt

* add batch size to inference table

* [slow-run] opt

* [run-slow] opt

---------

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Co-authored-by: Avishai Elmakies <avishai.elma@cs.huji.ac.il>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
Co-authored-by: chengchengpei <5881383+chengchengpei@users.noreply.github.com>
Co-authored-by: Isotr0py <2037008807@qq.com>
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Aarni Koskela <akx@iki.fi>
Co-authored-by: Titus von Koeller <9048635+Titus-von-Koeller@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Tibor Reiss <75096465+tibor-reiss@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>
Co-authored-by: Muhammad Naufil <m.naufil1@gmail.com>
Co-authored-by: sizhky <yyeshr@gmail.com>
Co-authored-by: Umar Butler <umar@umar.au>
Co-authored-by: Jonathan Mamou <jonathan.mamou@intel.com>
Co-authored-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com>
Co-authored-by: George Ohashi <george@neuralmagic.com>
Co-authored-by: Sara Adkins <sara@neuralmagic.com>
Co-authored-by: Sara Adkins <sara.adkins65@gmail.com>
Co-authored-by: Dipika Sikka <ds3822@columbia.edu>
Co-authored-by: Dipika <dipikasikka1@gmail.com>
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5 participants