GitLab

* Add nemotron support

* fix inference

* add unit test

* add layernorm1p as a class to avoid meta device mismatch

* test fixed

* Add copied_from statements

* remove pretraining_tp args

* remove nemotronlayernorm

* force LN computation done in FP32

* remove nemotrontokenizer and use llamatokenizer

* license update

* add option for kv_channels for minitron8b

* remove assert

* o_proj fixed

* o_proj reshape

* add gated_proj option

* typo

* remove todos

* fix broken test after merging latest main

* remove nezha/nat after meging main

* chnage default config to 15b model

* add nemo conversion script

* rename conversion script

* remove gate_proj option

* pr comment resolved

* fix unit test

* rename kv_channels to head_dim

* resolve PR issue

* add nemotron md

* fix broken tests

* refactor rope for nemotron

* test fix

* remove linearscaling

* whitespace and import

* fix some copied-from

* code style fix

* reformatted

* add position_embedding to nemotronattention

* rope refactor to only use config, copied-from fix

* format

* Run make fix-copies

* nemotron md with autodoc

* doc  fix

* fix order

* pass check_config_docstrings.py

* fix config_attributes

* remove all llama BC related code

* Use PreTrainedTokenizerFast

* ruff check examples

* conversion script update

* add nemotron to toctree

* BLIP preprocess

* BIT preprocess

* BRIDGETOWER preprocess

* CHAMELEON preprocess

* CHINESE_CLIP preprocess

* CONVNEXT preprocess

* DEIT preprocess

* DONUT preprocess

* DPT preprocess

* FLAVA preprocess

* EFFICIENTNET preprocess

* FUYU preprocess

* GLPN preprocess

* IMAGEGPT preprocess

* INTRUCTBLIPVIDEO preprocess

* VIVIT preprocess

* ZOEDEPTH preprocess

* VITMATTE preprocess

* VIT preprocess

* VILT preprocess

* VIDEOMAE preprocess

* VIDEOLLAVA

* TVP processing

* TVP fixup

* SWIN2SR preprocess

* SIGLIP preprocess

* SAM preprocess

* RT-DETR preprocess

* PVT preprocess

* POOLFORMER preprocess

* PERCEIVER preprocess

* OWLVIT preprocess

* OWLV2 preprocess

* NOUGAT preprocess

* MOBILEVIT preprocess

* MOBILENETV2 preprocess

* MOBILENETV1 preprocess

* LEVIT preprocess

* LAYOUTLMV2 preprocess

* LAYOUTLMV3 preprocess

* Add test

* Update tests

* add flash attention check

* fix

* fix

* add the missing marker

* bug fix

* add one more

* remove order

* add one more

Fixed tokenizertests for luke, mluke models.

* fix: persist embedding type of MBartConditonalGeneration after resize

* fix: persist embedding type of BartConditonalGeneration after resize

fix phi

* fix: SeamlessM4TFeatureExtractor stride remainder

* Added attention mask size test

* Reran ruff for style correction

* Remove size check between attn_weights and kv_seq_len

* add unit tests

* [whisper] compile compatibility with long-form decoding

* clarify comment

* fix after rebase

* finalise

* fix bsz

* fix cache split

* remove contiguous

* style

* finish

* update doc

* prevent cuda graph trace

* draft

* apply changes to all relevant archs

* rerun ci - check_docstrings.py failing?

* fix docstring

* move 2D->4D mask creation to modeling file

* repo consistency

* fix the batch size = 1 case - calling contiguous is not enough

* nit

* style

* propagate to gemma/gemma-2

* prepare inputs for gemma generation

* implement test and tiny fix in gemma2

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

* fix copies

* ci pass

* fix gemma's test_compile_static_cache tests

* flacky

* retrigger ci

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

* Fix FA2 call for Perciever layer

* [run_slow] idefics2

* [run_slow] idefics2

* [run_slow] idefics2

* Fix up

* [run_slow] idefics2

* [run_slow] idefics2

* [run_slow] idefics2

fix 💩

* enable flash-attn & static cache

* this works, not the prev

* fix for sliding window layers

* not needed anymore

* Remove user-defined tokens which can be obtained through merges

* Remove debug line

* formatting

* Refactor spm slow -> fast converter

* revert unnecessary refactor

* set comprehension

* remove test files

* Use `vocab_scores`

* Always replace spiece underline with space in decode

* we no longer need token filtering

* Add save fast load slow unit test

* Remove tokenizers version check

* Remove duplicate code

* Make `<start_of_turn>` and `<end_of_turn>` special tokens

* Bias merge priority with length if score is the same

* Add unit test for merge priority

* CI

* fix _fix_key in PreTrainedModel

* fix _find_longest_common_sequence

* add test

* remove result.json

* nit

* update test

* mvp

* added test (a few models need fixes)

* fix a few test cases

* test nits

* harder test 😈

* revert changes in stablelm

* test with improved condition

* add todo

* tmp commit

* merged with main

* nits

* add todo

* final corrections

* add docs for generation compilation

* docs nits

* add  tip

* PR suggestions

* add more details to the compilation docs

* fix cache positions

* cache is now init in generate; update docs

* tag test as flaky

* docs

* post rebase make fixup and other nits

* remove unintended changes

* whisper (encoder-decoder) not supported

* move token default updates to ; add tests for token defaults

* push changes

* manual rebase

* chameleon doesn't support this

* fix test_static_cache_mha_mqa_gqa (broken in another PR)

* docs: dynamic is better with end-to-end compilation

* Refactored to remove un-necessary object base class.

* small fix.

* llava w/o images

* tests

* fix

* [test_all] trigger full CI

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

fix E721 warnings

* [whisper] fix short-form output type

* add test

* make style

* update long-form tests

* fixes

* last fix

* finalise test

Replaced deprecated unittest method with the correct one.

* No more default chat templates

* Add the template to the GPT-SW3 tests since it's not available by default now

* Fix GPT2 test

* Fix Bloom test

* Fix Bloom test

* Remove default templates again

* relaxed rope check

* lets also accept rope_type=None, defaulting to the original implementation

* type and rope_type can coexist

* Updated ruff version and fixed the required code accorindg to the latest version.

* Updated ruff version and fixed the required code accorindg to the latest version.

* Added noqa directive to ignore 1 error shown by ruff

Revert "Incorrect Whisper long-form decoding timestamps  (#32003)"

This reverts commit cd48553f.

* renamed phi3 rope_scaling type

* fixed trailing whitespaces

* fixed test

* added warning

* fixed format

---------
Co-authored-by: Merve Noyan <mervenoyan@Merve-MacBook-Pro.local>

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Add YaRN and Dynamic-YaRN RoPE Scaling Methods

YaRN (Yet another RoPE extension method) combines the NTK-By-Parts
Interpolation and Attention Scaling methods, improving upon existing
RoPE interpolation methods for longer context window sizes.

Fine-tuned models maintain their original performance across benchmarks
while enabling efficient extrapolation and transfer learning for
quicker convergence, especially in compute-limited environments.

We implement YaRN and Dynamic-YaRN for the following list of models:

 - LLaMA
 - Falcon
 - GPT-NeoX
 - Olmo
 - Persimmon
 - Phi
 - StableLM
 - OpenLLaMA

New unit tests are added to assert YaRN's correct behavior on both
short and long sequence inputs.

For more details, please refer to https://arxiv.org/abs/2309.00071

.
Co-authored-by: Miguel Almeida <miguel.pessanha.almeida@tecnico.ulisboa.pt>

* Refactor YaRN implementation for LLaMA

Iterate on YaRN implementation for LLaMA and remove diff from remaining
models for increased PR modularity.

This commit includes the following changes:
- Merge 'yarn_rope_scaling' and 'rope_scaling' dictionaries
- Remove unnecessary attributes ('extrapolation_factor' and 'finetuned')
  from YaRN classes
- Inherit 'forward' method in YaRN classes from superclass
- Rename 'yarn' method to 'compute_yarn_scaling'
- Extend YaRN tests with further assertions
- Fix style inconsistencies
Co-authored-by: Miguel Monte e Freitas <miguelmontefreitas@tecnico.ulisboa.pt>

* Refactor Tensor Building Logic for YaRN

- Comply with the the tensor building logic introduced in #30743
- Add referencing to the optimized Attention Factor equation
- Remove Dynamic YaRN for a more agile deployment
Co-authored-by: mig-mfreitas <mig-mfreitas@users.noreply.github.com>

* remove unwanted file

---------
Co-authored-by: Miguel Almeida <miguel.pessanha.almeida@tecnico.ulisboa.pt>
Co-authored-by: mig-mfreitas <mig-mfreitas@users.noreply.github.com>
Co-authored-by: Joao Gante <joao@huggingface.co>

* fix mask creation of gpt2 and gpt_neox caused by me

* forgot the reshape of masks when shape > 2

* add tests for gpt neox and gpt2

* nit on a comment

* [whisper integration] use parquet dataset for testing

* propagate to others

* more propagation

* last one

* pad on right if training

* docs

* add tests

return assistant generated tokens mask in apply_chat_template

* Raised TypeError instead of ValueError for invalid types.

* Updated formatting using ruff.

* Retrieved few changes.

* Retrieved few changes.

* Updated tests accordingly.

* Fix failing test with race condition

* make fixup

* monotonic_ns instead of randint

* uuid4 instead of monotonic_ns

* Add a finally cleanup step

* remove is_shortform

* adapt _retrieve_max_frames_and_seek for short_form

* return bos token in short and long form

* add decoder_input_ids to short form audios

* add eos token for  short form

* handle short form token_timestamps

* no need to return scores

* add is_shortform conditions

* handle when max_new_tokens is None - short form

* handle assistant decoding

* fix

* handle return_dict_in_generate

* handle split_by_batch for encoder_attentions attribute

* handle num_beams>1

* handle num_return_sequences>1 in generate_with_fallback

* handle num_return_sequences>1 with return_dict_in_generate=True

* raise error if max_new_tokens + decoder_inputs_ids > max_target_pos

* fix

* apply review suggestions

* fix

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

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

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

* fix

* logits for both short form and long form

* handle if logits_processor is None

* test

* apply review changes to num_return_sequences

* add _expand_variables_for_generation

* remove short form commented section

* update comments

* uncomment num_beams line in generate_with_fallback

* update assistant decoding

* handle return_segment with short form generation

* up

* fix output format is_shortform

* overwrite beam_sample test

* update _set_return_timestamps

* apply review suggestions

* apply review suggestions

* remove seek_outputs_short_form

* fix _stack_split_outputs

* fix stack dim in _stack_split_outputs

* update tests

* fix past_key_values + beam tests

* fix

* clean _expand_variables_for_generation

* make style

* fix slow tests

* make style

* max_length condition

* make style

* add slow tests for shortform fallback

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

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

* apply review changes

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

* up

* fix slow tests

* apply review suggestions

* update test

* make style

* small fix

* fix

* fix test_new_cache_format

* fix past_key_values

* fix

* make style

* fix slow tests

* fix

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

* fix lo form timestamps in decode_batch

* Update src/transformers/models/whisper/tokenization_whisper.py
Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

* Update src/transformers/models/whisper/tokenization_whisper.py
Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

* add test

* make style

* fix copies

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

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

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

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

* apply review suggestions

* fix

* fix copies

* fix

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

* fix-copies

---------
Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>