GitLab

* aqlm init

* calibration and dtypes

* docs

* Readme update

* is_aqlm_available

* Simpler link in docs

* Test TODO real reference

* init _import_structure fix

* AqlmConfig autodoc

* integration aqlm

* integrations in tests

* docstring fix

* legacy typing

* Less typings

* More kernels information

* Performance -> Accuracy

* correct tests

* remoced multi-gpu test

* Update docs/source/en/quantization.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

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

* Brought back multi-gpu tests

* Update src/transformers/integrations/aqlm.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Update tests/quantization/aqlm_integration/test_aqlm.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

---------
Co-authored-by: Andrei Panferov <blacksamorez@yandex-team.ru>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Fix model documentation links in attention.md

* Fix external link syntax

* Fix target anchor names of section links

* Fix copyright statement comments

* Fix documentation headings

* Fix typos and grammar mistakes in docs and examples

* Fix typos in docstrings and comments

* Fix spelling of `tokenizer` in model tests

* Remove erroneous spaces in decorators

* Remove extra spaces in Markdown link texts

* squashed earlier commits for easier rebase

* rm rebase leftovers

* 4bit save enabled @quantizers

* TMP gptq test use exllama

* fix AwqConfigTest::test_wrong_backend for A100

* quantizers AWQ fixes

* _load_pretrained_model low_cpu_mem_usage branch

* quantizers style

* remove require_low_cpu_mem_usage attr

* rm dtype arg from process_model_before_weight_loading

* rm config_origin from Q-config

* rm inspect from q_config

* fixed docstrings in QuantizationConfigParser

* logger.warning fix

* mv is_loaded_in_4(8)bit to BnbHFQuantizer

* is_accelerate_available error msg fix in quantizer

* split is_model_trainable in bnb quantizer class

* rm llm_int8_skip_modules as separate var in Q

* Q rm todo

* fwd ref to HFQuantizer in type hint

* rm note re optimum.gptq.GPTQQuantizer

* quantization_config in __init__ simplified

* replaced NonImplemented with  create_quantized_param

* rm load_in_4/8_bit deprecation warning

* QuantizationConfigParser refactoring

* awq-related minor changes

* awq-related changes

* awq config.modules_to_not_convert

* raise error if no q-method in q-config in args

* minor cleanup

* awq quantizer docstring

* combine common parts in bnb process_model_before_weight_loading

* revert test_gptq

* .process_model_ cleanup

* restore dict config warning

* removed typevars in quantizers.py

* cleanup post-rebase 16 jan

* QuantizationConfigParser classmethod refactor

* rework of handling of unexpected aux elements of bnb weights

* moved q-related stuff from save_pretrained to quantizers

* refactor v1

* more changes

* fix some tests

* remove it from main init

* ooops

* Apply suggestions from code review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* fix awq issues

* fix

* fix

* fix

* fix

* fix

* fix

* add docs

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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

* Update docs/source/en/hf_quantizer.md

* address comments

* fix

* fixup

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

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

* address final comment

* update

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

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

* fix

* add kwargs update

* fixup

* add `optimum_quantizer` attribute

* oops

* rm unneeded file

* fix doctests

---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* add 4-bit serialization docs

* up

* up

* doc fix friday

* deprecated objects

* update not_doctested

* update toctree

streamline

* add sdpa

* wip

* cleaning

* add ref

* yet more cleaning

* and more :)

* wip llama

* working llama

* add output_attentions=True support

* bigcode sdpa support

* fixes

* gpt-bigcode support, require torch>=2.1.1

* add falcon support

* fix conflicts falcon

* style

* fix attention_mask definition

* remove output_attentions from attnmaskconverter

* support whisper without removing any Copied from statement

* fix mbart default to eager renaming

* fix typo in falcon

* fix is_causal in SDPA

* check is_flash_attn_2_available in the models init as well in case the model is not initialized through from_pretrained

* add warnings when falling back on the manual implementation

* precise doc

* wip replace _flash_attn_enabled by config.attn_implementation

* fix typo

* add tests

* style

* add a copy.deepcopy on the config in from_pretrained, as we do not want to modify it inplace

* obey to config.attn_implementation if a config is passed in from_pretrained

* fix is_torch_sdpa_available when torch is not installed

* remove dead code

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

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

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

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

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

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

* remove duplicate pretraining_tp code

* add dropout in llama

* precise comment on attn_mask

* add fmt: off for _unmask_unattended docstring

* precise num_masks comment

* nuke pretraining_tp in LlamaSDPAAttention following Arthur's suggestion

* cleanup modeling_utils

* backward compatibility

* fix style as requested

* style

* improve documentation

* test pass

* style

* add _unmask_unattended tests

* skip meaningless tests for idefics

* hard_check SDPA requirements when specifically requested

* standardize the use if XXX_ATTENTION_CLASSES

* fix SDPA bug with mem-efficient backend on CUDA when using fp32

* fix test

* rely on SDPA is_causal parameter to handle the causal mask in some cases

* fix FALCON_ATTENTION_CLASSES

* remove _flash_attn_2_enabled occurences

* fix test

* add OPT to the list of supported flash models

* improve test

* properly test on different SDPA backends, on different dtypes & properly handle separately the pad tokens in the test

* remove remaining _flash_attn_2_enabled occurence

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

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

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

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

* Update docs/source/en/perf_infer_gpu_one.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* remove use_attn_implementation

* fix docstring & slight bug

* make attn_implementation internal (_attn_implementation)

* typos

* fix tests

* deprecate use_flash_attention_2=True

* fix test

* add back llama that was removed by mistake

* fix tests

* remove _flash_attn_2_enabled occurences bis

* add check & test that passed attn_implementation is valid

* fix falcon torchscript export

* fix device of mask in tests

* add tip about torch.jit.trace and move bt doc below sdpa

* fix parameterized.expand order

* move tests from test_modeling_attn_mask_utils to test_modeling_utils as a relevant test class is already there

* update sdpaattention class with the new cache

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

* Update src/transformers/models/bark/modeling_bark.py

* address review comments

* WIP torch.jit.trace fix. left: test both eager & sdpa

* add test for torch.jit.trace for both eager/sdpa

* fix falcon with torch==2.0 that needs to use sdpa

* fix doc

* hopefully last fix

* fix key_value_length that has no default now in mask converter

* is it flacky?

* fix speculative decoding bug

* tests do pass

* fix following #27907

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

Update quantization.md

* v1 fusing modules

* add fused mlp support

* up

* fix CI

* block save_pretrained

* fixup

* small fix

* add new condition

* add v1 docs

* add some comments

* style

* fix nit

* adapt from suggestion

* add check

* change arg names

* change variables name

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

* style

* split up into 3 different private methods

* more conditions

* more checks

* add fused tests for custom models

* fix

* fix tests

* final update docs

* final fixes

* fix importlib metadata

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

* change it to `do_fuse`

* nit

* Update src/transformers/utils/quantization_config.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Update src/transformers/utils/quantization_config.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Update src/transformers/utils/quantization_config.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* few fixes

* revert

* fix test

* fix copies

* raise error if model is not quantized

* add test

* use quantization_config.config when fusing

* Update src/transformers/modeling_utils.py

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* first draft

* benchmarks

* feedback