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  1. 19 Mar, 2024 2 commits
    • StevenBucaille's avatar
      Implementation of SuperPoint and AutoModelForKeypointDetection (#28966) · 56baa033
      StevenBucaille authored 
      

* Added SuperPoint docs

* Added tests

* Removed commented part

* Commit to create and fix add_superpoint branch with a new branch

* Fixed dummy_pt_objects

* Committed missing files

* Fixed README.md

* Apply suggestions from code review

Fixed small changes
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Moved ImagePointDescriptionOutput from modeling_outputs.py to modeling_superpoint.py

* Removed AutoModelForKeypointDetection and related stuff

* Fixed inconsistencies in image_processing_superpoint.py

* Moved infer_on_model logic simply in test_inference

* Fixed bugs, added labels to forward method with checks whether it is properly a None value, also added tests about this logic in test_modeling_superpoint.py

* Added tests to SuperPointImageProcessor to ensure that images are properly converted to grayscale

* Removed remaining mentions of MODEL_FOR_KEYPOINT_DETECTION_MAPPING

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

* Fixed from (w, h) to (h, w) as input for tests

* Removed unnecessary condition

* Moved last_hidden_state to be the first returned

* Moved last_hidden_state to be the first returned (bis)

* Moved last_hidden_state to be the first returned (ter)

* Switched image_width and image_height in tests to match recent changes

* Added config as first SuperPointConvBlock init argument

* Reordered README's after merge

* Added missing first config argument to SuperPointConvBlock instantiations

* Removed formatting error

* Added SuperPoint to README's de, pt-br, ru, te and vi

* Checked out README_fr.md

* Fixed README_fr.md

* Test fix README_fr.md

* Test fix README_fr.md

* Last make fix-copies !

* Updated checkpoint path

* Removed unused SuperPoint doc

* Added missing image

* Update src/transformers/models/superpoint/modeling_superpoint.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Removed unnecessary import

* Update src/transformers/models/superpoint/modeling_superpoint.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Added SuperPoint to _toctree.yml

---------
Co-authored-by: default avatarsteven <steven.bucaillle@gmail.com>
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: default avatarSteven Bucaille <steven.bucaille@buawei.com>
      56baa033
    • Arthur's avatar
      [`GemmaConverter`] use user_defined_symbols (#29473) · 2f9a3edb
      Arthur authored 
      * use user_defined_symbols

* fixup

* nit

* add a very robust test

* make sure all models are tested with the `pretrained_tokenizer_to_test`

* should we make sure we test all of them?

* merge

* remove the id

* fix test

* update

* ousies

* oups

* fixup

* fix copies check

* remove `pretrained_tokenizer_to_test`
      2f9a3edb
  3. 18 Mar, 2024 1 commit
    • Yoach Lacombe's avatar
      Add MusicGen Melody (#28819) · c43b380e
      Yoach Lacombe authored 
      

* first modeling code

* make repository

* still WIP

* update model

* add tests

* add latest change

* clean docstrings and copied from

* update docstrings md and readme

* correct chroma function

* correct copied from and remove unreleated test

* add doc to toctree

* correct imports

* add convert script to notdoctested

* Add suggestion from Sanchit
Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* correct get_uncoditional_inputs docstrings

* modify README according to SANCHIT feedback

* add chroma to audio utils

* clean librosa and torchaudio hard dependencies

* fix FE

* refactor audio decoder -> audio encoder for consistency with previous musicgen

* refactor conditional -> encoder

* modify sampling rate logics

* modify license at the beginning

* refactor all_self_attns->all_attentions

* remove ignore copy from causallm generate

* add copied from for from_sub_models

* fix make copies

* add warning if audio is truncated

* add copied from where relevant

* remove artefact

* fix convert script

* fix torchaudio and FE

* modify chroma method according to feedback-> better naming

* refactor input_values->input_features

* refactor input_values->input_features and fix import fe

* add input_features to docstrigs

* correct inputs_embeds logics

* remove dtype conversion

* refactor _prepare_conditional_hidden_states_kwargs_for_generation ->_prepare_encoder_hidden_states_kwargs_for_generation

* change warning for chroma length

* Update src/transformers/models/musicgen_melody/convert_musicgen_melody_transformers.py
Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* change way to save wav, using soundfile

* correct docs and change to soundfile

* fix import

* fix init proj layers

* remove line breaks from md

* fix issue with docstrings

* add FE suggestions

* improve is in logics and remove useless imports

* remove custom from_pretrained

* simplify docstring code

* add suggestions for modeling tests

* make style

* update converting script with sanity check

* remove encoder attention mask from conditional generation

* replace musicgen melody checkpoints with official orga

* rename ylacombe->facebook in checkpoints

* fix copies

* remove unecessary warning

* add shape in code docstrings

* add files to slow doc tests

* fix md bug and add md to not_tested

* make fix-copies

* fix hidden states test and batching

---------
Co-authored-by: default avatarSanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
      c43b380e
  5. 15 Mar, 2024 2 commits
  7. 14 Mar, 2024 2 commits
  9. 13 Mar, 2024 5 commits
    • Nate Cibik's avatar
      Add PvT-v2 Model (#26812) · 1fc505b8
      Nate Cibik authored 
      

* Added pytests for pvt-v2, all passed

* Added pvt_v2 to docs/source/end/model_doc

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Reverted batch eval changes for PR

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat. Added additional type support for image size in config

* Fixed config backbone compat

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Reverted batch eval changes for PR

* Updated index.md

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat

* Ran fix-copies

* Fixed PvtV2Backbone tests

* Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py

* Fixed backbone stuff and fixed tests: all passing

* Ran make fixup

* Made modifications for code checks

* Remove ONNX config from configuration_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use explicit image size dict in test_modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Make image_size optional in test_modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove _ntuple use in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove reference to fp16_enabled

* Model modules now take config as first argument even when not used

* Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"

* All LayerNorm now instantiates with config.layer_norm_eps

* Added docstring for depth-wise conv layer

* PvtV2Config now only takes Union[int, Tuple[int, int]] for image size

* Refactored PVTv2 in prep for gradient checkpointing

* Gradient checkpointing ready to test

* Removed override of _set_gradient_checkpointing

* Cleaned out old code

* Applied code fixup

* Applied code fixup

* Began debug of pvt_v2 tests

* Leave handling of num_labels to base pretrained config class

* Deactivated gradient checkpointing tests until it is fixed

* Removed PvtV2ImageProcessor which duped PvtImageProcessor

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Added pvt_v2 to docs/source/end/model_doc

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Reverted batch eval changes for PR

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat. Added additional type support for image size in config

* Fixed config backbone compat

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* Set key and value layers to use separate linear modules. Fixed pruning function

* Set AvgPool to 7

* Fixed issue in init

* PvT-v2 now works in AutoModel

* Successful conversion of pretrained weights for PVT-v2

* Successful conversion of pretrained weights for PVT-v2 models

* Added pytests for pvt-v2, all passed

* Ran fix-copies and fixup. All checks passed

* Added additional ReLU for linear attention mode

* pvt_v2_b2_linear converted and working

* Reverted batch eval changes for PR

* Expanded type support for Pvt-v2 config

* Fixed config docstring. Added channels property

* Fixed model names in tests

* Fixed config backbone compat

* Ran fix-copies

* Fixed PvtV2Backbone tests

* Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py

* Fixed backbone stuff and fixed tests: all passing

* Ran make fixup

* Made modifications for code checks

* Remove ONNX config from configuration_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use explicit image size dict in test_modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Make image_size optional in test_modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove _ntuple use in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove reference to fp16_enabled

* Model modules now take config as first argument even when not used

* Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"

* All LayerNorm now instantiates with config.layer_norm_eps

* Added docstring for depth-wise conv layer

* PvtV2Config now only takes Union[int, Tuple[int, int]] for image size

* Refactored PVTv2 in prep for gradient checkpointing

* Gradient checkpointing ready to test

* Removed override of _set_gradient_checkpointing

* Cleaned out old code

* Applied code fixup

* Applied code fixup

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Ran fix-copies and fixup. All checks passed

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Reverted batch eval changes for PR

* Fixed config docstring. Added channels property

* Fixed config backbone compat

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Ran fix-copies and fixup. All checks passed

* Allowed for batching of eval metrics

* copied models/pvt to adapt to pvt_v2

* First commit of pvt_v2

* PvT-v2 now works in AutoModel

* Fixed config backbone compat

* Ran fix-copies

* Began debug of pvt_v2 tests

* Leave handling of num_labels to base pretrained config class

* Deactivated gradient checkpointing tests until it is fixed

* Removed PvtV2ImageProcessor which duped PvtImageProcessor

* Fixed issue from rebase

* Fixed issue from rebase

* Set tests for gradient checkpointing to skip those using reentrant since it isn't supported

* Fixed issue from rebase

* Fixed issue from rebase

* Changed model name in docs

* Removed duplicate PvtV2Backbone

* Work around type switching issue in tests

* Fix model name in config comments

* Update docs/source/en/model_doc/pvt_v2.md
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>

* Changed name of variable from 'attn_reduce' to 'sr_type'

* Changed name of variable from 'attn_reduce' to 'sr_type'

* Changed from using 'sr_type' to 'linear_attention' for clarity

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Removed old code

* Changed from using 'sr_type' to 'linear_attention' for clarity

* Fixed Class names to be more descriptive

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Removed outdated code

* Moved paper abstract to single line in pvt_v2.md

* Added usage tips to pvt_v2.md

* Simplified module inits by passing layer_idx

* Fixed typing for hidden_act in PvtV2Config

* Removed unusued import

* Add pvt_v2 to docs/source/en/_toctree.yml

* Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.

* Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Move function parameters to single line
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Update year of copyright to 2024
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py

Make code more explicit
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Updated sr_ratio to be more explicit spatial_reduction_ratio

* Removed excess type hints in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Move params to single line in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Removed needless comment in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update copyright date in pvt_v2.md
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Moved params to single line in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Updated copyright date in configuration_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Cleaned comments in modeling_pvt_v2.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Renamed spatial_reduction Conv2D operation

* Revert "Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
"

This reverts commit c4a04416dde8f3475ab405d1feb368600e0f8538.

* Updated conversion script to reflect module name change

* Deprecated reshape_last_stage option in config

* Removed unused imports

* Code formatting

* Fixed outdated decorators on test_inference_fp16

* Added "Copied from" comments in test_modeling_pvt_v2.py

* Fixed import listing

* Updated model name

* Force empty commit for PR refresh

* Fixed linting issue

* Removed # Copied from comments

* Added PVTv2 to README_fr.md

* Ran make fix-copies

* Replace all FoamoftheSea hub references with OpenGVLab

* Fixed out_indices and out_features logic in configuration_pvt_v2.py

* Made ImageNet weight conversion verification optional in convert_pvt_v2_to_pytorch.py

* Ran code fixup

* Fixed order of parent classes in PvtV2Config to fix the to_dict method override

---------
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      1fc505b8
    • Yih-Dar's avatar
      Fix `multi_gpu_data_parallel_forward` for `MusicgenTest` (#29632) · fe085560
      Yih-Dar authored 
      

update
Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
      fe085560
    • Raushan Turganbay's avatar
      Fix batching tests for new models (Mamba and SegGPT) (#29633) · 5ac264d8
      Raushan Turganbay authored 
      

* fix batchinng tests for new models

* Update tests/models/seggpt/test_modeling_seggpt.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      5ac264d8
    • Lysandre Debut's avatar
      Adds pretrained IDs directly in the tests (#29534) · 11bbb505
      Lysandre Debut authored 
      * Adds pretrained IDs directly in the tests

* Fix tests

* Fix tests

* Review!
      11bbb505
    • bytebarde's avatar
      [Flash Attention 2] Add flash attention 2 for GPT-J (#28295) · be3fd8a2
      bytebarde authored 
      

* initial implementation of flash attention for gptj

* modify flash attention and overwrite test_flash_attn_2_generate_padding_right

* update flash attention support list

* remove the copy line in the `CodeGenBlock`

* address copy mechanism

* Update src/transformers/models/gptj/modeling_gptj.py
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>

* Add GPTJ attention classes

* add expected outputs in the gptj test

* Ensure repo consistency with 'make fix-copies'

---------
Co-authored-by: default avatarYounes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      be3fd8a2
  11. 12 Mar, 2024 2 commits
  13. 11 Mar, 2024 1 commit
  15. 08 Mar, 2024 2 commits
  17. 07 Mar, 2024 3 commits
  19. 05 Mar, 2024 5 commits
    • Arthur's avatar
      [`Add Mamba`] Adds support for the `Mamba` models (#28094) · fb1c62e9
      Arthur authored 
      

* initial-commit

* start cleaning

* small nits

* small nits

* current updates

* add kernels

* small refactoring little step

* add comments

* styling

* nit

* nits

* Style

* Small changes

* Push dummy mambda simple slow

* nit

* Use original names

* Use original names and remove norm

* Updates for inference params

* Style nd updates

* nits

* Match logits

* Add a test

* Add expected generated text

* nits doc, imports and styling

* style

* oups

* dont install kernels, invite users to install the required kernels

* let use use the original packages

* styling

* nits

* fix some copieds

* update doc

* fix-copies

* styling done

* nits

* fix import check

* run but wrong cuda ress

* mamba CUDA works :)

* fix the fast path

* config naming nits

* conversion script is not required at this stage

* finish fixing the fast path: generation make sense now!

* nit

* Let's start working on the CIs

* style

* better style

* more nits

* test nit

* quick fix for now

* nits

* nit

* nit

* nit

* nits

* update test rest

* fixup

* update test

* nit

* some fixes

* nits

* update test values

* fix styling

* nit

* support peft

* integrations tests require torchg

* also add slow markers

* styling

* chose forward wisely

* nits

* update tests

* fix gradient checkpointing

* fixup

* nit

* fix doc

* check copies

* fix the docstring

* fix some more tests

* style

* fix beam search

* add init schene

* update

* nit

* fix

* fixup the doc

* fix the doc

* fixup

* tentative update but slow is no longer good

* nit

* should we always use float32?

* nits

* revert wrong changes

* res in float32

* cleanup

* skip fmt for now

* update generation values

* update test values running original model

* fixup

* update tests + rename inference_params to cache_params + make sure training does not use cache_params

* small nits

* more nits

* fix final CIs

* style

* nit doc

* I hope final doc nits

* nit

* 🫠

* final touch!

* fix torch import

* Apply suggestions from code review
Co-authored-by: default avatarLysandre Debut <hi@lysand.re>

* Apply suggestions from code review

* fix fix and fix

* fix base model prefix!

* nit

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

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

* nit

---------
Co-authored-by: default avatarLysandre Debut <hi@lysand.re>
      fb1c62e9
    • Arthur's avatar
      [`Udop imports`] Processor tests were not run. (#29456) · 4d892b72
      Arthur authored 
      * fix udop imports

* sort imports
      4d892b72
    • Arthur's avatar
      Revert-commit 0d52f9f5 (#29455) · 57d007b9
      Arthur authored 
      * style

* revert with RP

* nit

* exact revert
      57d007b9
    • Arthur Zucker's avatar
      more fix · 0d52f9f5
      Arthur Zucker authored
      0d52f9f5
    • Arthur's avatar
      [`UdopTokenizer`] Fix post merge imports (#29451) · 13285220
      Arthur authored 
      * update

* ...

* nits

* arf

* 🧼

* beat the last guy

* style everyone
      13285220
  21. 04 Mar, 2024 3 commits
    • NielsRogge's avatar
      Add UDOP (#22940) · 836921fd
      NielsRogge authored 
      

* First draft

* More improvements

* More improvements

* More fixes

* Fix copies

* More improvements

* More fixes

* More improvements

* Convert checkpoint

* More improvements, set up tests

* Fix more tests

* Add UdopModel

* More improvements

* Fix equivalence test

* More fixes

* Redesign model

* Extend conversion script

* Use real inputs for conversion script

* Add image processor

* Improve conversion script

* Add UdopTokenizer

* Add fast tokenizer

* Add converter

* Update README's

* Add processor

* Add fully fledged tokenizer

* Add fast tokenizer

* Use processor in conversion script

* Add tokenizer tests

* Fix one more test

* Fix more tests

* Fix tokenizer tests

* Enable fast tokenizer tests

* Fix more tests

* Fix additional_special_tokens of fast tokenizer

* Fix tokenizer tests

* Fix more tests

* Fix equivalence test

* Rename image to pixel_values

* Rename seg_data to bbox

* More renamings

* Remove vis_special_token

* More improvements

* Add docs

* Fix copied from

* Update slow tokenizer

* Update fast tokenizer design

* Make text input optional

* Add first draft of processor tests

* Fix more processor tests

* Fix decoder_start_token_id

* Fix test_initialization

* Add integration test

* More improvements

* Improve processor, add test

* Add more copied from

* Add more copied from

* Add more copied from

* Add more copied from

* Remove print statement

* Update README and auto mapping

* Delete files

* Delete another file

* Remove code

* Fix test

* Fix docs

* Remove asserts

* Add doc tests

* Include UDOP in exotic model tests

* Add expected tesseract decodings

* Add sentencepiece

* Use same design as T5

* Add UdopEncoderModel

* Add UdopEncoderModel to tests

* More fixes

* Fix fast tokenizer

* Fix one more test

* Remove parallelisable attribute

* Fix copies

* Remove legacy file

* Copy from T5Tokenizer

* Fix rebase

* More fixes, copy from T5

* More fixes

* Fix init

* Use ArthurZ/udop for tests

* Make all model tests pass

* Remove UdopForConditionalGeneration from auto mapping

* Fix more tests

* fixups

* more fixups

* fix the tokenizers

* remove un-necessary changes

* nits

* nits

* replace truncate_sequences_boxes with truncate_sequences for fix-copies

* nit current path

* add a test for input ids

* ids that we should get taken from c9f7a32f57440d90ff79890270d376a1cc0acb68

* nits converting

* nits

* apply ruff

* nits

* nits

* style

* fix slow order of addition

* fix udop fast range as well

* fixup

* nits

* Add docstrings

* Fix gradient checkpointing

* Update code examples

* Skip tests

* Update integration test

* Address comment

* Make fixup

* Remove extra ids from tokenizer

* Skip test

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

* Update year

* Address comment

* Address more comments

* Address comments

* Add copied from

* Update CI

* Rename script

* Update model id

* Add AddedToken, skip tests

* Update CI

* Fix doc tests

* Do not use Tesseract for the doc tests

* Remove kwargs

* Add original inputs

* Update casting

* Fix doc test

* Update question

* Update question

* Use LayoutLMv3ImageProcessor

* Update organization

* Improve docs

* Update forward signature

* Make images optional

* Remove deprecated device argument

* Add comment, add add_prefix_space

* More improvements

* Remove kwargs

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Co-authored-by: default avatarArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: default avatarArthur <48595927+ArthurZucker@users.noreply.github.com>
      836921fd
    • Donggeun Yu's avatar
      DeformableDETR support bfloat16 (#29232) · ed74d978
      Donggeun Yu authored 
      

* Update ms_deform_attn_cuda.cu

* Update ms_deform_attn_cuda.cuh

* Update modeling_deformable_detr.py

* Update src/transformers/models/deformable_detr/modeling_deformable_detr.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update modeling_deformable_detr.py

* python utils/check_copies.py --fix_and_overwrite

* Fix dtype missmatch error

* Update test_modeling_deformable_detr.py

* Update test_modeling_deformable_detr.py

* Update modeling_deformable_detr.py

* Update modeling_deformable_detr.py

* Support DeformableDETR with bfloat16

* Add test code

* Use AT_DISPATCH_FLOATING_TYPES_AND2

Use AT_DISPATCH_FLOATING_TYPES_AND2

* Update tests/models/deformable_detr/test_modeling_deformable_detr.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/deformable_detr/test_modeling_deformable_detr.py
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix not found require_torch_bf16 function

---------
Co-authored-by: default avataramyeroberts <22614925+amyeroberts@users.noreply.github.com>
      ed74d978
    • Nick DeGroot's avatar
      Fix OneFormer `post_process_instance_segmentation` for panoptic tasks (#29304) · 8ef98628
      Nick DeGroot authored 
      * 🐛 Fix oneformer instance post processing when using panoptic task type

* ✅

 Add unit test for oneformer instance post processing panoptic bug

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Co-authored-by: default avatarNick DeGroot <1966472+nickthegroot@users.noreply.github.com>
      8ef98628
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