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

deps_2

* 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

fix: add new llava like model bug

* draft

* updates

* works?

* try adding python example in hidden section

* another try

* hwo do i render python

* format as html code?

* Update docs/source/en/kv_cache.md
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update docs/source/en/kv_cache.md
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update docs/source/en/kv_cache.md
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update docs/source/en/kv_cache.md
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update docs/source/en/kv_cache.md
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* one more small update

* should render hidden secrtion now

* add outputs

* fix links

* check links

* update all links

* update with offloaded cache

* all cache is importable, so they appear in docs

* fix copies

* docstring...

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Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Respect the config's attn if set

* Update test - can override in from_config

* Fix

Fixed tokenizertests for luke, mluke models.

* fix: persist embedding type of MBartConditonalGeneration after resize

* fix: persist embedding type of BartConditonalGeneration after resize

I always forget what typical values are, and I have to look at the paper everytime. This will be a helpful reminder.

* save total_vocab_size = vocab_size + user added tokens to speed up operation

* updating length when added_tokens_decoder is set

* add test len(tokenizer)

fix phi

* fix: SeamlessM4TFeatureExtractor stride remainder

* Added attention mask size test

* Reran ruff for style correction

Bump keras in /examples/research_projects/decision_transformer

Bumps [keras](https://github.com/keras-team/keras) from 2.8.0 to 2.13.1.
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](https://github.com/keras-team/keras/compare/v2.8.0...v2.13.1

)

---
updated-dependencies:
- dependency-name: keras
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

MixtralFlashAttention2: put "plus 1" inside parentheses when calculating rotary_seq_len, allowing None position_ids input. (#31500)

* Mixtral: remove unnecessary plus 1 when calculating rotary_seq_len, allowing position_ids=None (no auto position_ids generation could be unsafe)

* fix typo [:-1] to [:, -1]

* to meet formatting requirement

* to meet formatting requirement

* remove white space

* MixtralFlashAttention2: put "+ 1" inside parentheses when calculating rotary_seq_len, allowing None position_ids input. Fix format/style issue.

* propagate to startcoder2, phi3, mixtral and qwen2

* update qwen2_moe

fix: (issue #32124) Exception raised when running `transformers/examples/flax/language-modeling/t5_tokenizer_model.py`. (#32157)

fix: Exception raised when running .

* up

* style

* stopping

tests! :D

nits

* Test this zach

* Test for improper init w/o zero3

* Move back

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

* Get rid of stars in warning

* Make private

* Make clear

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

* fixed hybrid cache init, added test

* Fix Test Typo

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Co-authored-by: Aaron Haag <aaron.haag@siemens.com>

* Initial implementation of OffloadedCache

* enable usage via cache_implementation

* Address feedback, add tests, remove legacy methods.

* Remove flash-attn, discover synchronization bugs, fix bugs

* Prevent usage in CPU only mode

* Add a section about offloaded KV cache to the docs

* Fix typos in docs

* Clarifications and better explanation of streams

* Fix conflicting key in init kwargs in PreTrainedTokenizerBase

* Update code to check for callable key in save_pretrained

* Apply PR suggestions

* Invoke CI

* Updates based on PR suggestion

empty list in defaults

* Remove TPU device map for saving tokenizer config

* Update tokenization_utils_base.py

* Fix error msg when passing non-string device into tokenizer

* Fix error message for non-string tokenizer device

* Print out tokenizer device type in error msg

* Update tokenization_utils_base.py

Co-authored-by: Guoming Zhang <37257613+nv-guomingz@users.noreply.github.com>

* 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

cache class flag

* Fixed staticmethods with self as first argument.

* Fixed staticmethods with self as first argument.

* Fixed staticmethods with self as first argument.

* Fixed staticmethods with self as first argument.

* 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 error when streaming agent run to gradio with non-string tool arguments