GitLab

* inital commit

* update

* update conversion checkpoint

* update conversion script

* nits

* some fixes

* nits

* merge

* fix permute

* nits

* fix

* nits

* nits

* nits

* fix rope

* fix both rope

* nites

* style

* make sure flax works

* fix flax init code

* fix foward

* nits

* print flax generation out

* current code

* nits

* SIIIIIIIIIIIIIIIIIII

* update

* add new tokenizer

* correct fast tokenizer

* fix conversion

* more comments

* fix modeling and conversion

* nits and nits

* nits testing

* add some tokenization tests

* add some edge cases

* add slow tests and fix them

* fixup

* fix copies for modeling

* fix copies

* add 7B slow tests

* fix

* fix

* fix tests

* make tokenizer cis go green

* styling

* last tokenizer nits

* update jax tests

* fix flax for 7b

* add jit testing 🤗



* cleanups

* isolated nit, inv_freq for rotary_emb.inv_freq

* propagate to jax

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* adjust test

* fix conversion script

* change name

* correct file names

* update conversion script

* Fix bos and eos token ids in the model configuration (#3)

* update modelling

* update conversion script

* add static cache for gemma

* fix sdpa generate

* fix batched

* multiple fixes

* fix FA2

* final fix

* Rename a few missing strings and filenames (#4)

* merge with upstream main

* fix copies

* fix copies

* fix fixup

* fix fixup

* fix

* fix

* final tests

* fix fx gemma tests

* fix fx bf16/fp16 tests

* update slow fx tests

* fx slow tests: one logits, one generation

* move jit test standalone

* Apply suggestions from code review

* nits

* tokenizer updates

* more tokenization updates: custom GemmaSentencepieceExtrator

* style

* Update src/transformers/cache_utils.py

* Update src/transformers/models/gemma/__init__.py

* Update tests/models/gemma/test_modeling_flax_gemma.py

* small nits

* style

* update tokenization test

* fix the rotary embedding

* with style

* fix slow tests

* WARNING this commit might be very important for precisions

* Update tests/models/gemma/test_modeling_flax_gemma.py

* Update src/transformers/models/gemma/configuration_gemma.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Update src/transformers/models/gemma/modeling_flax_gemma.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* small nits here and there!

* forgotten nit

* remove on the fly computation of inv_freq

* revert previous change, let's be safe and for now re-compute freq cis to make sure it's in float

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_flax_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_tokenization_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_tokenization_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_tokenization_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_tokenization_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update tests/models/gemma/test_modeling_gemma.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* nit conversion script link

* fix some tests

* add not doctest and pr doctest

* repo consistency

* fix last CIs 🚀



* update all readmes

---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Add resource

* Add more resources

* Add resources

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

* Remove mention

* Remove pipeline tags

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

* Script & Manual edition

* Update

* First draft

* Add CLIPForImageClassification

* Remove scripts

* Fix doctests

* Add `StableLM`

* fix(model): re-create from `huggingface-cli add-new-model-like persimmon`

* fix: re-add changes to address comments

* fix(readme): add links to paper

* fix(tokenization_auto): remove `GPTNeoXTokenizerFastFast` ref

* fix(tests): re-add `@slow` decorator to integration tests

* fix(tests): import slow...

* fix(readme_hd): remove whitespace edit

* fix(tokenizer): auto tokenizer tuple

* skip doctests for `modeling_stablelm`

Add language identifiers to code blocks

* 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

* This is a test commit

* testing commit

* final commit with some changes

* Removed copy statement

* Fixed formatting issues

* Fixed error added past_key_values in the forward method

* Fixed a trailing whitespace. Damn the formatting rules are strict

* Added the copy statement

* 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

* Adding [T5/MT5/UMT5]ForTokenClassification

* Add auto mappings for T5ForTokenClassification and variants

* Adding ForTokenClassification to the list of models

* Adding attention_mask param to the T5ForTokenClassification test

* Remove outdated comment in test

* Adding EncoderOnly and Token Classification tests for MT5 and UMT5

* Fix typo in umt5 string

* Add tests for all the existing MT5 models

* Fix wrong comment in dependency_versions_table

* Reverting change to common test for _keys_to_ignore_on_load_missing

The test is correctly picking up redundant keys in _keys_to_ignore_on_load_missing.

* Removing _keys_to_ignore_on_missing from MT5 since the key is not used in the model

* Add fix-copies to MT5ModelTest

* direct copy from llama work

* mistral modules forward pass working

* flax mistral forward pass with sliding window

* added tests

* added layer collection approach

* Revert "added layer collection approach"

This reverts commit 0e2905bf2236ec323163fc1a9f0c016b21aa8b8f.

* Revert "Revert "added layer collection approach""

This reverts commit fb17b6187ac5d16da7c461e1130514dc3d137a43.

* fixed attention outputs

* added mistral to init and auto

* fixed import name

* fixed layernorm weight dtype

* freeze initialized weights

* make sure conversion consideres bfloat16

* added backend

* added docstrings

* added cache

* fixed sliding window causal mask

* passes cache tests

* passed all tests

* applied make style

* removed commented out code

* applied fix-copies ignored other model changes

* applied make fix-copies

* removed unused functions

* passed generation integration test

* slow tests pass

* fixed slow tests

* changed default dtype from jax.numpy.float32 to float32 for docstring check

* skip cache test  for FlaxMistralForSequenceClassification since if pad_token_id in input_ids it doesn't score previous input_ids

* updated checkpoint since from_pt not included

* applied black style

* removed unused args

* Applied styling and fixup

* changed checkpoint for doc back

* fixed rf after adding it to hf hub

* Add dummy ckpt

* applied styling

* added tokenizer to new ckpt

* fixed slice format

* fix init and slice

* changed ref for placeholder TODO

* added copies from Llama

* applied styling

* applied fix-copies

* fixed docs

* update weight dtype reconversion for sharded weights

* removed Nullable input ids

* Removed unnecessary output attentions in Module

* added embedding weight initialziation

* removed unused past_key_values

* fixed deterministic

* Fixed RMS Norm and added copied from

* removed input_embeds

* applied make style

* removed nullable input ids from sequence classification model

* added copied from GPTJ

* added copied from Llama on FlaxMistralDecoderLayer

* added copied from to FlaxMistralPreTrainedModel methods

* fix test deprecation warning

* freeze gpt neox random_params and fix copies

* applied make style

* fixed doc issue

* skipped docstring test to allign # copied from

* applied make style

* removed FlaxMistralForSequenceClassification

* removed unused padding_idx

* removed more sequence classification

* removed sequence classification

* applied styling and consistency

* added copied from in tests

* removed sequence classification test logic

* applied styling

* applied make style

* removed freeze and fixed copies

* undo test change

* changed repeat_kv to tile

* fixed to key value groups

* updated copyright year

* split casual_mask

* empty to rerun failed pt_flax_equivalence test FlaxWav2Vec2ModelTest

* went back to 2023 for tests_pr_documentation_tests

* went back to 2024

* changed tile to repeat

* applied make style

* empty for retry on Wav2Vec2

* [Whisper] Make tokenizer normalization public

* add to docs

* [Docs] Fix Typo in English CLIP model_doc

* [Docs] Fix Typo in Japanese CLIP model_doc

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* Add docs

* Remove file

* Add copied from

* Address comments

* Address comments

* Address comments

* Fix style

* Update docs

* Convert all checkpoints, add integration test

* Rename checkpoints

* Add pretrained backbone attributes

* Fix default config

* Address comment

* Add figure to docs

* Fix bug thanks to @xenova

* Update conversion script

* Fix integration test

Co-authored-by: Pashmina Cameron <11311835+pashminacameron@users.noreply.github.com>

First draft

* first commit

* correct default value non causal

* update config and modeling code

* update converting checkpoint

* clean modeling and fix tests

* make style

* add new config parameters to docstring

* fix copied from statements

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* make position_embeddings_type docstrings clearer

* clean converting script

* remove function not used

* clean modeling file

* apply suggestion for test file + add convert script to not_doctested

* modify tests according to review - cleaner logic and more tests

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

* add checker of valid position embeddings type

* instantiate new layer norm layer with the right eps

* fix freeze_feature_encoder since it can be None in some cases

* add test same output in convert script

* restore wav2vec2conformer and add new model

* create processor and FE + clean

* add new model code

* fix convert script and set default config parameters

* correct model id paths

* make style

* make fix-copies and cleaning files

* fix copied from statements

* complete .md and fixe copies

* clean convert script argument defaults

* fix config parameters docstrings

* fix config docstring

* add copied from and enrich FE tests

* fix copied from and repo-consistency

* add autotokenizer

* make test input length shorter and change docstring code

* fix docstrings and copied from

* add add_adapter to ASR training example

* make testing of adapters more robust

* adapt to multi adapter layers

* refactor input_values->input_features and remove w2v2-bert feature extractor

* remove pretraining model

* remove depreciated features and useless lines

* add copied from and ignore statements to modeling tests

* remove pretraining model #2

* change import in convert script

* change default in convert script

* update readme and remove useless line

* Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* refactor BERT to Bert for consistency

* remove useless ignore copy statement

* add persistent to buffer in rotary

* add eps in LayerNorm init and remove copied from

* add adapter activation parameters and add copied from statements

* Fix copied statements and add unitest.skip reasons

* add copied statement in test_processor

* refactor processor

* make style

* replace numpy random by torch rand

* remove expected output CTC

* improve converting script with processor class

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

* remove gumbel class

* remove tests related to previously deleted class

* Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* correct typos

* remove uused parameters

* update processor to takes both text and audio

* update checkpoints

* update expected output and add ctc expected output

* add label_attention_mask

* replace pt with np in processor tests

* fix typo

* revert to behaviour with labels_attention_mask

---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add config, modeling, and tokenization

* add auto and init

* update readme

* update readme

* update team name

* fixup

* fixup

* update config

* update code style

* update for fixup

* update for fixup

* update for fixup

* update for testing

* update for testing

* fix bug for config and tokenization

* fix bug for bos token

* not doctest

* debug tokenizer

* not doctest

* debug tokenization

* debug init for tokenizer

* fix style

* update init

* delete if in token auto

* add tokenizer doc

* add tokenizer in init

* Update dummy_tokenizers_objects.py

* update

* update

* debug

* Update tokenization_qwen2.py

* debug

* Update convert_slow_tokenizer.py

* add copies

* add copied from and make style

* update files map

* update test

* fix style

* fix merge reading and update tests

* fix tests

* fix tests

* fix style

* debug a variable in readme

* Update src/transformers/models/qwen2/configuration_qwen2.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* update test and copied from

* fix style

* update qwen2 tokenization  and tests

* Update tokenization_qwen2.py

* delete the copied from after property

* fix style

* update tests

* update tests

* add copied from

* fix bugs

* update doc

* add warning for sliding window attention

* update qwen2 tokenization

* fix style

* Update src/transformers/models/qwen2/modeling_qwen2.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix tokenizer fast

---------
Co-authored-by: Ren Xuancheng <jklj077@users.noreply.github.com>
Co-authored-by: renxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix(phi): Phi does not use softmax_scale in Flash-Attention.

* chore(docs): Update Phi docs.

Fix URL to Ai Sweden Models reference and model loading

* update docs

* added Tip

* Add first draft

* Use appropriate gelu function

* More improvements

* More improvements

* More improvements

* Convert checkpoint

* More improvements

* Improve docs, remove print statements

* More improvements

* Add link

* remove unused masking function

* begin tokenizer

* do_lower_case

* debug

* set split_special_tokens=True

* Remove script

* Fix style

* Fix rebase

* Use same design as CLIP

* Add fast tokenizer

* Add SiglipTokenizer to init, remove extra_ids

* Improve conversion script

* Use smaller inputs in conversion script

* Update conversion script

* More improvements

* Add processor to conversion script

* Add tests

* Remove print statements

* Add tokenizer tests

* Fix more tests

* More improvements related to weight initialization

* More improvements

* Make more tests pass

* More improvements

* More improvements

* Add copied from

* Add canonicalize_text

* Enable fast tokenizer tests

* More improvements

* Fix most slow tokenizer tests

* Address comments

* Fix style

* Remove script

* Address some comments

* Add copied from to tests

* Add more copied from

* Add more copied from

* Add more copied from

* Remove is_flax_available

* More updates

* Address comment

* Remove SiglipTokenizerFast for now

* Add caching

* Remove umt5 test

* Add canonicalize_text inside _tokenize, thanks Arthur

* Fix image processor tests

* Skip tests which are not applicable

* Skip test_initialization

* More improvements

* Compare pixel values

* Fix doc tests, add integration test

* Add do_normalize

* Remove causal mask and leverage ignore copy

* Fix attention_mask

* Fix remaining tests

* Fix dummies

* Rename temperature and bias

* Address comments

* Add copied from to tokenizer tests

* Add SiglipVisionModel to auto mapping

* Add copied from to image processor tests

* Improve doc

* Remove SiglipVisionModel from index

* Address comments

* Improve docs

* Simplify config

* Add first draft

* Make it like mistral

* More improvements

* Fix attention_mask

* Fix output_attentions

* Add note in docs

* Convert multilingual model

* Convert large checkpoint

* Convert more checkpoints

* Add pipeline support, correct image_mean and image_std

* Use padding=max_length by default

* Make processor like llava

* Add code snippet

* Convert more checkpoints

* Set keep_punctuation_string=None as in OpenCLIP

* Set normalized=False for special tokens

* Fix doc test

* Update integration test

* Add figure

* Update organization

* Happy new year

* Use AutoModel everywhere

---------
Co-authored-by: patil-suraj <surajp815@gmail.com>

* add segmentation map processing to sam image processor

* fixup

* add tests

* reshaped_input_size is shape before padding

* update tests for size/shape outputs

* fixup

* add code snippet to docs

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

* Add missing backticks

* add `segmentation_maps` as arg for SamProcessor.__call__()

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

* start - docs, SpeechT5 copy and rename

* add relevant code from FastSpeech2 draft, have tests pass

* make it an actual conformer, demo ex.

* matching inference with original repo, includes debug code

* refactor nn.Sequentials, start more desc. var names

* more renaming

* more renaming

* vocoder scratchwork

* matching vocoder outputs

* hifigan vocoder conversion script

* convert model script, rename some config vars

* replace postnet with speecht5's implementation

* passing common tests, file cleanup

* expand testing, add output hidden states and attention

* tokenizer + passing tokenizer tests

* variety of updates and tests

* g2p_en pckg setup

* import structure edits

* docstrings and cleanup

* repo consistency

* deps

* small cleanup

* forward signature param order

* address comments except for masks and labels

* address comments on attention_mask and labels

* address second round of comments

* remove old unneeded line

* address comments part 1

* address comments pt 2

* rename auto mapping

* fixes for failing tests

* address comments part 3 (bart-like, train loss)

* make style

* pass config where possible

* add forward method + tests to WithHifiGan model

* make style

* address arg passing and generate_speech comments

* address Arthur comments

* address Arthur comments pt2

* lint  changes

* Sanchit comment

* add g2p-en to doctest deps

* move up self.encoder

* onnx compatible tensor method

* fix is symbolic

* fix paper url

* move models to espnet org

* make style

* make fix-copies

* update docstring

* Arthur comments

* update docstring w/ new updates

* add model architecture images

* header size

* md wording update

* make style

* fix fa2

* fix FA2 for popular models

* improve warning and add Younes as co-author
Co-Authored-By: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

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

* fix the warning

* Add Tip

* typo fix

* nit

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

Fix mistral link in mixtral.md

Update mixtral.md

correct minor typo in overview

* Update vipllava.md

* Update modeling_vipllava.py

* [Seamless] Fix links in docs

* apply suggestions from code review

* v1

* add-new-model-like

* revert

* fix forward and conversion script

* revert

* fix copies

* fixup

* fix

* Update docs/source/en/index.md

* Apply suggestions from code review

* push

* fix

* fixes here and there

* up

* fixup and fix tests

* Apply suggestions from code review

* add docs

* fixup

* fixes

* docstring

* add docstring

* fixup

* docstring

* fixup

* nit

* docs

* more copies

* fix copies

* nit

* update test

Update formats

fix parameter count in readme

* up

* up

* test

* logits ok

* up

* up

* few fixes

* conversion script

* up

* nits

* nits

* update

* nuke

* more updates

* nites

* fix many issues

* nit

* scatter

* nit

* nuke megablocks

* nits

* fix conversion script

* nit

* remove

* nits

* nit

* update

* oupsssss

* change

* nits device

* nits

* fixup

* update

* merge

* add copied from

* fix the copy mentions

* update tests

* more fixes

* nits

* conversion script

* add parts of the readme

* Update tests/models/mixtral/test_modeling_mixtral.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* new test + conversion script

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

* Apply suggestions from code review

* fix

* fix copies

* fix copies

* ooops

* fix config

* Apply suggestions from code review

* fix nits

* nit

* add copies

* add batched tests

* docs

* fix flash attention

* let's add more verbose

* add correct outputs

* support router ouptus

* ignore copies where needed

* fix

* cat list if list is given for now

* nits

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

* finish router refactoring

* fix forward

* fix expected values

* nits

* fixup

* fix

* fix bug

* fix

* fix dtype mismatch

* fix

* grrr grrr I support item assignment

* fix CI

* docs

* fixup

* remove some copied form

* fix weird diff

* skip doctest fast on the config and modeling

* mark that is supports flash attention in the doc

* update

* Update src/transformers/models/mixtral/modeling_mixtral.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Update docs/source/en/model_doc/mixtral.md
Co-authored-by: Lysandre Debut <hi@lysand.re>

* revert router logits config issue

* update doc accordingly

* Update src/transformers/models/mixtral/convert_mixtral_weights_to_hf.py

* nits

* use torch testing asssert close

* fixup

* doc nits

---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>

* More improvements

* Improve variable names

* Update READMEs, improve docs

* 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

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

* add model like

* logits match

* minor fixes

* fixes

* up

* up

* add todo

* llava processor

* keep the processor simple

* add conversion script

* fixup

* fix copies

* up

* add to index

* fix config + logits

* fix

* refactor

* more refactor

* more refactor

* fix copies

* add authors

* v1 tests

* add `LlavaProcessor` in init

* remove unneeded import

* up

* up

* docs

* up

* fix CI

* fix CI

* add attention  mask in test

* make fixup

* remove the vision model

* that' s the dirty way to do it

* nits

* nits

* updates

* add more tests

* add input tests

* fixup

* more styling

* nits

* updates amd cleanup

* fixup the generation expected results

* fix the testing script

* some cleanup and simplification which does not work yet but almost there!

* make correct dispatch operations

* vectorize works for batch of images and text

* last todos

* nits

* update test and modeling code

* remove useless function for now

* fix few issues

* fix generation

* some nits

* add bakllava

* nits

* remove duplicated code

* finis merge

* cleanup

* missed this line

* fill the todos

* add left padding offset

* add left and rignt padding logic

* bool to properly index

* make sure

* more cleanups

* batch is fixed 😉



* add correct device for tensor creation

* fix some dtype missmatch

* ruff

* update conversion script

* Update src/transformers/__init__.py

* fa 2 support + fix conversion script

* more

* correct reshaping

* fix test dict

* fix copies by ignoring

* fix nit

* skip clip vision model

* fixup

* fixup

* LlavaForVisionText2Text -> LlavaForCausalLM

* update

* fix

* raise correct errors

* fix

* docs

* nuke for now

* nits here and there

* fixup

* fix remaining tests

* update LlavaForConditionalGeneration instead of CausalLM

* fixups

* pipeline support

* slow and piepline tests

* supports batch

* nits

* cleanup

* fix first integration tests

* add pad token where needed

* correct etsts

* fixups

* update pipeline testr

* fix quality

* nits

* revert unneeded change

* nit

* use BatchFeature

* from ...feature_extraction_utils import BatchFeature

* nits

* nits

* properly update

* more f*** nits

* fix copies

* comment

* keep slow test slow

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

* add piepline example

* add pixel values in docstrign

* update pr doctest

* fix

* fix slow tests

* remove hack

* fixup

* small note

* forward contrib credits from PR25789

* forward contrib credits from original implementation and work

* add arthur

* Update src/transformers/models/llava/processing_llava.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* update docstring

* nit

* move to not doctested because of timeout issues

* fixup

* add description

* more

* fix-copies

* fix docs

* add beam search

* add more comments

* add typehints on processor

* add speedup plot

* update slow tests and docs

* push test

* push batched test

* fix batched generation with different number of images

* remove benchmark due to a bug

* fix test

* fix copies

* add gcolab demo

---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: shauray8 <shauray8@users.noreply.github.com>
Co-authored-by: haotian-liu <haotian-liu@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>

* add FA and modify doc file

* test_flash_attn_2_generate_padding_right test overwritten

* comment

* modify persimmon modeling file

* added speedup graph

* more changes

* Copies `modeling_flax_gpt_neo.py` to start

* MLP Block. WIP Attention and Block

* Adds Flax implementation of `LlamaMLP`
Validated with in-file test.
Some slight numeric differences, but assuming it isn't an issue

* Adds `FlaxLlamaRMSNorm` layer
`flax.linen` includes `RMSNorm` layer but not necessarily in all
versions. Hence, we add in-file.

* Adds FlaxLlamaAttention
Copied from GPT-J as it has efficient caching implementation as well as
rotary embeddings.
Notice numerically different, but not by a huge amount. Needs
investigating

* Adds `FlaxLlamaDecoderLayer`
numerically inaccurate, debugging..

* debugging rotary mismatch
gptj uses interleaved whilst llama uses contiguous
i think they match now but still final result is wrong.
maybe drop back to just debugging attention layer?

* fixes bug with decoder layer
still somewhat numerically inaccurate, but close enough for now

* adds markers for what to implement next
the structure here diverges a lot from the PT version.
not a big fan of it, but just get something working for now

* implements `FlaxLlamaBlockCollection`]
tolerance must be higher than expected, kinda disconcerting

* Adds `FlaxLlamaModule`
equivalent PyTorch model is `LlamaModel`
yay! a language model🤗

* adds `FlaxLlamaForCausalLMModule`
equivalent to `LlamaForCausalLM`
still missing returning dict or tuple, will add later

* start porting pretrained wrappers
realised it probably needs return dict as a prereq

* cleanup, quality, style

* readds `return_dict` and model output named tuples

* (tentatively) pretrained wrappers work 🔥

* fixes numerical mismatch in `FlaxLlamaRMSNorm`
seems `jax.lax.rsqrt` does not match `torch.sqrt`.
manually computing `1 / jax.numpy.sqrt` results in matching values.

* [WIP] debugging numerics

* numerical match
I think issue was accidental change of backend. forcing CPU fixes test.
We expect some mismatch on GPU.

* adds in model and integration tests for Flax Llama
summary of failing:
- mul invalid combination of dimensions
- one numerical mismatch
- bf16 conversion (maybe my local backend issue)
- params are not FrozenDict

* adds missing TYPE_CHECKING import and `make fixup`

* adds back missing docstrings
needs review on quality of docstrings, not sure what is required.
Furthermore, need to check if `CHECKPOINT_FOR_DOC` is valid. See TODO

* commenting out equivalence test as can just use common

* debugging

* Fixes bug where mask and pos_ids were swapped in pretrained models
This results in all tests passing now 🔥



* cleanup of modeling file

* cleanup of test file

* Resolving simpler review comments

* addresses more minor review comments

* fixing introduced pytest errors from review

* wip additional slow tests

* wip tests
need to grab a GPU machine to get real logits for comparison
otherwise, slow tests should be okay

* `make quality`, `make style`

* adds slow integration tests
- checking logits
- checking hidden states
- checking generation outputs

* `make fix-copies`

* fix mangled function following `make fix-copies`

* adds missing type checking imports

* fixes missing parameter checkpoint warning

* more finegrained 'Copied from' tags
avoids issue of overwriting `LLAMA_INPUTS_DOCSTRING`

* swaps import guards
??? how did these get swapped initially?

* removing `inv_freq` again as pytorch version has now removed

* attempting to get CI to pass

* adds doc entries for llama flax models

* fixes typo in __init__.py imports

* adds back special equivalence tests
these come from the gpt neo flax tests. there is special behaviour for these models that needs to override the common version

* overrides tests with dummy to see if CI passes
need to fill in these tests later

* adds my contribution to docs

* `make style; make quality`

* replaces random masking with fixed to work with flax version

* `make quality; make style`

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* updates `x`->`tensor` in `rotate_half`

* addresses smaller review comments

* Update docs/source/en/model_doc/llama.md
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* adds integration test class

* adds `dtype` to rotary embedding to cast outputs

* adds type to flax llama rotary layer

* `make style`

* `make fix-copies`

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* applies suggestions from review

* Update modeling_flax_llama.py

* `make fix-copies`

* Update tests/models/llama/test_modeling_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_flax_llama.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* fixes shape mismatch in FlaxLlamaMLP

* applies some suggestions from reviews

* casts attn output logits to f32 regardless of dtype

* adds attn bias using `LlamaConfig.attention_bias`

* adds Copied From comments to Flax Llama test

* mistral and persimmon test change -copy from llama

* updates docs index

* removes Copied from in tests

it was preventing `make fix-copies` from succeeding

* quality and style

* ignores FlaxLlama input docstring

* adds revision to `_CHECKPOINT_FOR_DOC`

* repo consistency and quality

* removes unused import

* removes copied from from Phi test

now diverges from llama tests following FlaxLlama changes

* adds `_REAL_CHECKPOINT_FOR_DOC`

* removes refs from pr tests

* reformat to make ruff happy

---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>