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add back self.max_position_embeddings = config.max_position_embeddings #33550

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chengchengpei
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@chengchengpei chengchengpei commented Sep 17, 2024

What does this PR do?

Fix hiyouga/LLaMA-Factory#5461

Fixes # (issue)

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chengchengpei commented Sep 18, 2024

@zucchini-nlp ^^ can you take a look at this change? Thanks ^^

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@chengchengpei I am not sure why the error is being raised, as the new RoPE doesn't need any position embeddings in its init. Am I missing smth?

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@chengchengpei I am not sure why the error is being raised, as the new RoPE doesn't need any position embeddings in its init. Am I missing smth?

@zucchini-nlp thanks for your reply :)

I am new to transformers.

i used llama-factory to fine tune. last week, it works. but yesterday, i saw some errors described in hiyouga/LLaMA-Factory#5461

i tracked the code changes and found self.max_position_embeddings = config.max_position_embeddings was removed currently. i can run the finetune again after i added it back.
if self.max_position_embeddings = config.max_position_embeddings is not required, how to fix the errors i saw in hiyouga/LLaMA-Factory#5461 ? thanks for your help.

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I see, just for my own understanding wanted to know where exactly the attribute is being accessed. I'll try to reproduce it later :)

Thanks for fixing this! It is in line with Llama and seems to be causing bugs while tuning, so we can have it back

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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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Okay, cc @gante to take into account if we refactor

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@zucchini-nlp

thanks.

when this PR can be merged?

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Yes, sorry. I was off for a while, merging :)

@zucchini-nlp zucchini-nlp merged commit 214db9e into huggingface:main Sep 23, 2024
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avishaiElmakies pushed a commit to avishaiElmakies/transformers that referenced this pull request Sep 25, 2024
huggingface#33550)

* add back self.max_position_embeddings = config.max_position_embeddings

* fix-copies
amyeroberts pushed a commit to amyeroberts/transformers that referenced this pull request Oct 2, 2024
huggingface#33550)

* add back self.max_position_embeddings = config.max_position_embeddings

* fix-copies
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>
NielsRogge added a commit to NielsRogge/transformers that referenced this pull request Oct 21, 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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AttributeError: 'Qwen2Attention' object has no attribute 'max_position_embeddings'
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