GitLab

fixes

* fix merging

* make chameleon conditional

* Chameleon model integration
Co-authored-by: Jacob Kahn <jacobkahn1@gmail.com>
Co-authored-by: Leonid Shamis <leonid.shamis@gmail.com>

* fix 7B, again. mask away image tokens

* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* remove pretrained_config_map

* make fixup passing up to utils/check_config_docstrings.py; vqgan moved to the modeling file

* remove tokenizer (use llama's); remove codechameleon tests

* a few copied from statements and minor changes

* copied from in ChameleonModel

* some copies in ChameleonForCausalLM

* a few more copies

* VQModel moved to ChameleonModel (as opposed to being in the processor)

* ChameleonProcessor ready

* Fix chameleon weights convert

* update conversion script

* clean-up processing

* update modeling a bit

* update

* update (throws error...)

* correct conversion ready

* fix tests

* fix docs

* docs

* ve swin norm

* fix device for vocab map

* add normalization

* update

* update script with rope rotations

* final fix on model conversion

* add slow tests

* more info in docs

* fix repo consistency tests

* fix repo tests

* fix-copies

* hope this will make CI happy

* fix for 30b model

* Update docs/source/en/index.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/chameleon.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* Update docs/source/en/model_doc/chameleon.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/chameleon.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/chameleon.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update docs/source/en/model_doc/chameleon.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

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

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

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

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

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

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

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

* Update tests/models/chameleon/test_modeling_chameleon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/chameleon/test_modeling_chameleon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/chameleon/test_modeling_chameleon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* address comments

* remove assertion in conversion script

* add image processor test

* not copied

* port changes for qk layernorm

* fix-copies

* read token decorator for tests

* [run-slow] chameleon

* one more read-token

* address some comments

* qk norm changes

* tests and repo check

* moved rope permutations to conversion, YAY!

* fix past kv check

* docs

* layernorm done!

* let's be consistent in naming

* fix slow tests

* weird thing with slow CI, but let's see

* once more try

* remove past-kv as tuple following llama

* ignore

* style

---------
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
Co-authored-by: ArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: jacobkahn <jacobkahn1@gmail.com>
Co-authored-by: Leonid Shamis <leonid.shamis@gmail.com>
Co-authored-by: Leonid Shamis <lshamis@meta.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* tmp commit

* shorter

* nit

* explicit kwargs

* propagate changes

* mass propagation with a few manual touches (let's see how CI behaves)

* fix cacheless case

* Update src/transformers/generation/utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* make fixup

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

* dumb commit

* nit

* update

* something like this

* unpack in modeling utils

* safe import

* oups

* update

* nits

* diff convert gemma

* update

* start propagating

* udpate other modeling code as well

* update for sliding window models

* nits

* more init cleanups

* styling

* fixup

* noice

* pass fixup

* typo typing_extension -> typing_extensions

* torch.nn.functionnal -> torch.nn.functional

* add to import structure

* unpack

* simplify a bit more for this first version

* nut

* update

* update

* nit

* ease the import of `Unpack`

* remove useless `use_sliding_window`

* no qua please

* protect import?

* style

* [run-slow]

* [run slow] llama,gemma,mistral,mixtral

* remove extra kwargs

* fix llama

* address review comments

* apply diff_model_converter to modeling_gemma.py

* remove cache_position 1

* remove cache_position 2

* some cleaning

* refactor gemma2 as well

* apply review comments

* rename file to modeling_flash_attention_utils.py

* siglip refactor

* remove dead code

* is the hub down?

* still down?

* fix siglip

* fix gemma2

* fatal: Could not read from remote repository.

* fix typo in softcap implem

* flacky

* Failed: Timeout >120.0s

---------
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>

* fix llama fsdp

* fixup

* adding FSDP tests for CPU offloading

* fixes

* fix tests

* fix tests

* add it for mixtral

* propagate the changes on other models

* Update src/transformers/models/phi/modeling_phi.py

* Delete utils/testing_scripts/fsdp_cpu_offloading.py

Remove script - FSDP + CPU offloading it tested in the test suite

* Delete utils/testing_scripts/dummy_fsdp_config.yml

* Update + add cache_positions docstring

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

* tmp

* update models

* revert utils

* delete

* Update src/transformers/models/dbrx/modeling_dbrx.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* modify warning msg

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

* Update modeling_qwen2.py

* Fix llama

* More fixes

* Fix contrastive_search for new cache structure, and improve performance by removing inneficient torch.stack(torch.split(x, top_k, dim=0))

* Fix _contrastive_search for non-standard cache using ellipsis slicing

* Fix all outputs.logits memory leaks for all decoding strategies!

* Fix small error in _contrastive_search()

* Make all necessary change and revert for the new class

* Apply coding style

* Remove pipes in type hints for compatibility

* correct type hint

* apply style

* Use DynamicCache by default and solve conflicts

* Fix rebase issues

* Add `_supports_dynamic_cache_class` in models for models that support DynamicCache but not other caches to make DynamicCache the default for more models

* Create generation config to return legacy format by default, or to choose not to

* style

* Fix case when use_cache is False

* Remove default DynamicCache in assiste_decoding if assistant_model does not support it + fix _seen_tokens when cropping cache

* Update prepare_inputs_for_generation() for case with empty DynamicCache

* Correct return of args in _assisted_decoding

* Remove EfficientDynamicCache as it is no longer needed

* Correct mistake in generation config

* Move cache logic of assisted decoding to AssistedCandidateGenerator.__init__

* change DynamicCache function names from "split" to "batch_split" for readability + apply coding style

* Remove `_supports_dynamic_cache_class` attribute after rebase

* Correct missing line lost in conflict resolution during rebasing

* Add special case for Jamba

* Fix jamba test

* Coding style

* coding style

* Correct missing import in rebasing

* Simplify _validate_model_kwargs based on removal of _supports_dynamic_cache attribute

* Simplify code paths in _contrastive_search

* coding style

* Update docstrings of cache methods

* Update prepare_inputs_for_generation() -> past_key_values are always Cache objects

* fixes

* fix-copies

* current working example!

* commit regex and result file

* update

* nit

* push the conversion file

* oups

* roadmap and nits

* attempt diffs for 3 files

* persimmon

* nit

* add diff file that is the same as the modeling_llama.py

* fix rope nits

* updates

* updates with converted versions

* give some breathing space to the code

* delete

* update

* update

* push the actual result

* update regex patterns

* update regex patterns

* fix some issues

* fix some issues

* fix some issues

* updates

* updates

* updates

* updates

* updates

* revert changes done to llama

* updates

* update gemma

* updates

* oups

* current state

* current state

* update

* ouiiii

* nit

* clear diffs

* nit

* fixup

* update

* doc 🚀

* 🔥

* for now use gemma

* deal with comments

* style

* handle funtions

* deal with assigns

* todos

* process inheritage

* keep decorators?

* 🤗

* deal with duplicates

* fixup

* correctly remove duplicate code

* run ruff post script

* ruff deals pretty well with imports, let's leave it to him

* ah maybe not lol

* for now remove all imports from child.

* nit

* conversion of llama

* okay

* convert starcoder2

* synch with main

* update llama diff

* updates

* https://docs.astral.sh/ruff/rules/redefined-while-unused/

 fixes the imports, bit needs later version of ruff

* updates

* okay actual state

* non zero exit

* update!

* revert unrelated

* remove other diff files

* updates

* cleanup

* update

* less diff!

* stash

* current updates

* updates

* No need for call

* finished fining deps

* update

* current changes

* current state

* current state

* new status

* nit

* finally

* fixes

* nits

* order is now expected

* use logger info instead of prints

* fixup

* up

* nit

* update

* nits

* update

* correct merge

* update

* update

* update

* add warning

* update caution message

* update

* better merging strategy

* copy class statements :wink

* fixups

* nits

* update

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* nits

* smaller header

* do cleanup some stuff

* even simpler header?

* fixup

* updates

* ruff

* update examples

* nit

* TODO

* state

* OUUUUUUF

* current state

* nits

* final state

* add a readme

* fixup

* remove diff llama

* fix

* nit

* dummy noy funny

* ruff format tests src utils --check

* everless diffs

* less diffs and fix test

* fixes

* naming nit?

* update converter and add supper example

* nits

* updated for function signatures

* update

* update

* add converted dummies

* autoformat

* single target assign fix

* fixup

* fix some imports

* fixes

* don't push them

* `# noqa: F841`

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

* clean-up

* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/cache_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fixup

* Update tests/quantization/quanto_integration/test_quanto.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* more suggestions

* mapping if torch available

* run tests & add 'support_quantized' flag

* fix jamba test

* revert, will be fixed by another PR

* codestyle

* HQQ and versatile cache classes

* final update

* typo

* make tests happy

---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* first version

* fix sliding window

* fix style

* add sliding window cache

* fix style

* address comments

* fix test

* fix style

* move sliding window check inside cache init

* revert changes on irrelevant files & add comment on SlidingWindowCache

* address comments & fix style

fix style

* update causal mask

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] llama

* [run-slow] mistral

* [run-slow] mistral

* [run-slow] mistral

* revert CI from a10 to t4

* wrap up

* add torch.compile dynamic support

* Add SDPA dynamic shapes compile test & improve SDPA comment

* comment consistency

* Add MistralForTokenClassification

* Add tests and docs

* Add token classification for Mixtral and Qwen2

* Save llma for token classification draft

* Add token classification support for Llama, Gemma, Persimmon, StableLm and StarCoder2

* Formatting

* Add token classification support for Qwen2Moe model

* Add dropout layer to each ForTokenClassification model

* Add copied from in tests

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Propagate suggested changes

* Style

---------
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Remove deprecated logic and warnings

* Add back some code that seems to be important...

* Let's just add all he nllb stuff back; removing it is a bit more involved

* Remove kwargs

* Remove more kwargs

* jamba cache

* new flag

* generate exception

* Fix llama model forward function with attention=True, same-length encoded sequence.

* Fix style

* propagate fix to modeling_cohere, gemma, dbrx, and olmo (which copy the same sdpa masking logic from llama)

* Fix style

* ignore unnecessary sdpa mask converter when output_attentions=True

* add tests checking sdpa and eager outputs match when output_attentions=True

* Split if statements in two lines
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix formatting

* Add fix to new jetmoe model

* Add missing output_attentions argument to jetmoe mask creation

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

* 4d mask fixes

* Update custom 4D mask logic

* test moved to mixin

* extra tests 4d mask

* upd 4d mask and StaticCache handling

* added Mask4DTestHard to mistral tests

* post-rebase fixes

* test fixes for StaticCache

* make fix-copies

* upd 1 after #30476

* fix common tests

* rm elif attention_mask.dim() == 4:

* tests combined, fixed, mixtral supported

* bigbird style chg reverted

* rm if attention_mask.dim() == 2

* modeling_llama formatting chg

---------
Co-authored-by: Joao Gante <joao@huggingface.co>

kv_cache is no longer a model attribute

* add bias

* fix quality

* Reenable SDPA's FA2 during training with torch.compile

* fix Olmo's SDPA FA2 dispatching too

* update formatting

* improved SDPA comment

* formatting and explanatory comment

* is_causal if statement to one-liner

* nit to make sure cache positions are not sliced

* fix other models

* nit

* style

FIX: Fixes unexpected behaviour for Llava / LLama & AWQ Fused modules + revert #30070 at the same time (#30317)

* Update awq.py

* style

* revert felix PR

* fix

* add felix comments

* Revert "Re-enable SDPA's FA2 path (#30070)"

This reverts commit 05bdef16.

* Revert "Fix quality Olmo + SDPA (#30302)"

This reverts commit ec92f983.

* tentatively re-enable FA2 + SDPA

* better comment

* _ignore_causal_mask_sdpa as staticmethod

* type hints

* use past_seen_tokens instead

* enable copied from for sdpa

* ruff

* llama simplifications on review

* remove unnecessary self.is_causal check

* fix copies

* cleaning

* precise message

* better doc

* add test

* simplify

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* style

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

* [WIP] fix fx

* [WIP] fix fx

* [WIP] fix fx

* [WIP] fix fx

* [WIP] fix fx

* Apply changes to other models

fix awq quant

* fi xbc?

* nit

* always convert the mask

* rebase and fix copies

* attempt to fix

* the actual fix that works with compilation!

* this?

* temporary update

* nit?

* dispatcg to memory efficient?

* update both models that have static cache support

* fix copies fix compile

* make sure fix

* fix cohere and gemma

* fix beams?

* nit

* slipped through the cracks

* nit

* nits

* update

* fix-copies

* skip failing tests

* nits

* partial 4d masks

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* fix stablelm dropout argument type error

* fix docs of _flash_attention_forward

* fix all docs of _flash_attention_forward

* fix docs of _flash_attention_forward in starcoder2

---------
Co-authored-by: oliang <oliang@tencent.com>

* Fix: Disable torch.autocast in RotaryEmbedding of Gemma and LLaMa for MPS devices

* Update src/transformers/models/gemma/modeling_gemma.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update llama ang gemma rope use cpu in mps device

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