GitLab

* 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

* Rebase to main

* Fix attention implementation autoset for tex and vision configs

* Fixup

* Minor fixes

* Fix copies

* Fix attention_mask for FA2

* Add eqvivalence tests for siglip

* Remove right padding test

* Uncomment flaky

* Fix import

* Add to docs

* Fix test message

* Add sdpa

* Add sdpa equivalence test

* Add siglip sdpa to docs

* Fix typing for attention output

* Add sdpa tests

* Fix signature of FA2

* Autoset attn_implementation in config

* Rename bsz -> batch_size

* Move back autoset attn method

* Mark as flaky

* Correct attention mask padding

* [run-slow] siglip

* Add FA2 and sdpa docs

* Style fix

* Remove flaky for FA2 test

* Change attention implementation set

* Change attn_implementaiton propogation

* Fix typos

* Add modality to assert message

* Add more sdpa backends in test

* [run slow] siglip

* Add math sdpa backend for all options

* [run slow] siglip

* Add siglip loss function

* Update docs

* Enable training tests
[experimental] enable GC training tests as it has worked for my own data

* Remove test_training* overrides to enable training tests
[run_slow] siglip

* Skip training tests for Siglip text model and ImageClassificationModel
[run_slow] siglip

* Skip GC training tests for SiglipForImageClassification

* Explicitly skip training tests for SiglipVisionModel
Add skip reason for training tests for SiglipTextModel

* Remove copied from to fix CI

* Skip tests properly

* [test_all]

* Add 'reason' as kwarg for skipTest

* [test_all] Fix up

* [test_all]

* device-map siglip

* move split modules to PretrainedSigLip

* Draft fast image processors

* Draft working fast version

* py3.8 compatible cache

* Enable loading fast image processors through auto

* Tidy up; rescale behaviour based on input type

* Enable tests for fast image processors

* Smarter rescaling

* Don't default to Fast

* Safer imports

* Add necessary Pillow requirement

* Woops

* Add AutoImageProcessor test

* Fix up

* Fix test for imagegpt

* Fix test

* Review comments

* Add warning for TF and JAX input types

* Rearrange

* Return transforms

* NumpyToTensor transformation

* Rebase - include changes from upstream in ImageProcessingMixin

* Safe typing

* Fix up

* convert mean/std to tesnor to rescale

* Don't store transforms in state

* Fix up

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

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

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

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

* Warn if fast image processor available

* Update src/transformers/models/vit/image_processing_vit_fast.py

* Transpose incoming numpy images to be in CHW format

* Update mapping names based on packages, auto set fast to None

* Fix up

* Fix

* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test

* Update src/transformers/models/vit/image_processing_vit_fast.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Add equivalence and speed tests

* Fix up

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

* Rename to test_model_common_attributes
The method name is misleading - it is testing being able to get and set embeddings, not common attributes to all models

* Explicitly skip

* Fix accelerate tests

* fix clip

* skip dbrx tests

* fix GPTSan

* fix M2M100Model

* same fix as jamba

* fix mt5

* Fix T5Model

* Fix umt5 model

* fix switch_transformers

* fix whisper

* fix gptsan again

* fix siglip recent test

* skip siglip tests

* wrong place fixed

* update ruff version

* fix research projects

* Empty

* Fix errors

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Co-authored-by: Lysandre <lysandre@huggingface.co>

* Add interpolate positional encoding to siglip

* Change # of patches for siglip interpolation test

* fix formatting

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

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

* [test_all] Remove static pretrained maps from the library's internals

* Deprecate archive maps instead of removing them

* Revert init changes

* [test_all] Deprecate instead of removing

* [test_all] PVT v2 support

* [test_all] Tests should all pass

* [test_all] Style

* Address review comments

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

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

* [test_all] trigger tests

* [test_all] LLAVA

* [test_all] Bad rebase

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

* Adds pretrained IDs directly in the tests

* Fix tests

* Fix tests

* Review!

* add tests for batching support

* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* fixes and comments

* use cosine distance for conv models

* skip mra model testing

* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* finzalize  and make style

* check model type by input names

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

* fixed batch size for all testers

* Revert "fixed batch size for all testers"

This reverts commit 525f3a0a058f069fbda00352cf202b728d40df99.

* add batch_size for all testers

* dict from model output

* do not skip layoutlm

* bring back some code from git revert

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

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

* clean-up

* where did minus go in tolerance

* make whisper happy

* deal with consequences of losing minus

* deal with consequences of losing minus

* maskformer needs its own test for happiness

* fix more models

* tag flaky CV models from Amy's approval

* make codestyle

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

* First draft

* Add CLIPForImageClassification

* Remove scripts

* Fix doctests

* 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

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