GitLab

* benchmark

* update

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

If required padding for a crop larger than input image is odd-numbered,
the padding would be rounded down instead of rounded up, causing the
output dimension to be one smaller than it should be.

* Enforce saving at end of training

* Fix test

* Rework test

* Fixup tests'

* Update comment based on sourab feedback

* Clean

* add fix

* update import

* updated dicts and comments

* remove prints

* Update testing_utils.py

Update processing_paligemma.py

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

* add V1 - adalomo not working yet

* add todo docs + refactor from comments

* adjust LR

* add docs

* add more elaborated test

* Apply suggestions from code review
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

* fix

* push

* add accelerate check

* fix DDP case

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

* fix

* init kwargs

* safely add attribute

* revert to enum logic

* Update src/transformers/trainer.py

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

Update test_modeling_mistral.py

* add model_memory_anatomy to es/_toctree.yml

* copy model_memory_anatomy.md to es/

* translate first section

* translate doc

* chage forward activations

* fix sentence and and link to Trainer

* fix Trainer link

* 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

* Introduce configured_state

* Include note on tuning

* Allow for users to have defined a state already

* Include tests

* Add note on hpam tune

* Guard a bit better

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

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

* Finish rebase

* Finish rebase

* Guard carefully

* Fixup test

* Refactor

* Fin refactor

* Comment

* Update wrt feedback

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

propagate changes to more models

* fix typos and one shape comment

* fix `intermediade` typo in jamba

* Add AutoFeatureExtractor support to Wav2Vec2ProcessorWithLM

* update with a type filter

* add raises error test

* fix added test

* fix for custom pipeline configuration

* fix for custom pipelines

* remove extra exception

* added test for custom pipelines extra tag

* format with ruff

* limit extra tag for first time only

* format with ruff

* improve tests for custom pipelines

* Fix similar bug in processor (related to #30193)

* Reformat processing_git.py to comply with ruff formatting

Fix num_hidden_layers in initialization

Originally, the initialization was using config.num_layers instead of config.num_hidden_layers. This fixes that.

* compute num_frames in WhisperFeatureExtractor

* add return_num_frames in WhisperFeatureProcessor + adapt pipeline

* return_timestamps renaming + pipeline fix

* fix

* fix

* fix

* add tests

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

* apply review changes

* fix

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

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

* apply review

* fix

* review changes

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

* make style quality

* EXPECTED_OUTPUT in single line

* small numpy->torch fix

* fix

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

Update modeling_deformable_detr.py

* update docs with batch ex

* Update docs/source/en/model_doc/llava_next.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* accept nested list of img

---------
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* add torch.compile dynamic support

* Add SDPA dynamic shapes compile test & improve SDPA comment

* comment consistency

* Update Dockerfile

* Update docker/transformers-quantization-latest-gpu/Dockerfile

* 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>

* add interpolation of positional encoding support to swin

* add style changes

* use default image processor and make size a dictionary
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* Refactor image size validation logic when interpolation is disabled
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* remove asserts in modeling
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add dynamic resolution input support to swinv2

* change size to ensure interpolation encoding path is triggered

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* set interpolate_pos_encoding default value to False

* add dynamic resolution input to donut swin

* add dynamic resolution input to maskformer swin

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

* Add resize and pad strategy

* Merge get_size functions

* Add pad_size + tests to object detection models

* Fixup

* Update docstrings

* Fixup

* update release script

* update release script

* Support arbitrary processor

* fix

* nit

* update

* nit

* nit

* fix and revert

* add a small test

* better check

* fixup

* bug so let's just use class for now

* oups

* .

* [whisper] fix multilingual fine-tuning

* config ids as well

* fix: missing dependencies

* fix: image classification dependencies

* added_no_split_modules

* added LlavaNextVisionAttention to _no_split_modules

* 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

* add llama logits test

* fix

* fix tests
"

"

* fix for a10

* format

* format

* fix

* [run-slow] remove fmt: skip

* Your commit message

* test commit

* Revert "test commit"

This reverts commit b66e01e55f5e31d4c0479cac4bcacc0f123dc9d2.

* [run-slow]llama

* Update tests/models/llama/test_modeling_llama.py

* [run-slow]llama

* empty commit

* Fix VideoLlava imports

* Update dummy objects

Reverting to 2.2.1

fix model id in docs

* fix

* [run-slow] gemma

* add test

* add `test_compile_static_cache`

* fix

* style

* remove subprocess

* use attribute

* fix

* style

* update

* [run-slow] dbrx,gemma,jetmoe,phi3,recurrent_gemma

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

* disable fa

* disable fa

* update warning

* update warning

* jamba cache

* new flag

* generate exception