GitLab

* Add image processor to trainer

* Replace tokenizer=image_processor everywhere

Trainer with PyTorch now requires accelerate to be installed.

Partly resolves huggingface/transformers#29174

* 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: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

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

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

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

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

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

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

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

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

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

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

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

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

* Cleaned comments in modeling_pvt_v2.py
Co-authored-by: amyeroberts <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: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* First draft

* Add CLIPForImageClassification

* Remove scripts

* Fix doctests

* pull and push updates

* add docs

* fix modeling

* Add and run test

* make copies

* add task

* fix tests and fix small issues

* Checks on a Pull Request

* fix docs

* add desc pvt.md

* First draft

* More improvements

* Convert patch embedding layer

* Convert all weights

* Make conversion work

* Improve conversion script

* Fix style

* Make all tests pass

* Add image processor to auto mapping

* Add swiglu ffn

* Add image processor to conversion script

* Fix conversion of giant model

* Fix documentation

* Fix style

* Fix tests

* Address comments

* Address more comments

* Remove unused arguments

* Remove more arguments

* Rename parameters

* Include mask token

* Address comments

* Add docstring

* Transfer checkpoints

* Empty commit

* Rename index.mdx to index.md

* With saved modifs

* Address review comment

* Treat all files

* .mdx -> .md

* Remove special char

* Update utils/tests_fetcher.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

---------
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

Update image_classification.mdx

* generated code from add-new-model-like

* Add code for modeling, config, and weight conversion

* add tests for image-classification, update modeling and config

* add code, tests for semantic-segmentation

* make style, make quality, make fix-copies

* make fix-copies

* Update modeling_mobilevitv2.py

fix bugs

* Update _toctree.yml

* update modeling, config

fix bugs

* Edit docs - fix bug MobileViTv2v2 -> MobileViTv2

* Update mobilevitv2.mdx

* update docstrings

* Update configuration_mobilevitv2.py

make style

* Update convert_mlcvnets_to_pytorch.py

remove unused options

* Update convert_mlcvnets_to_pytorch.py

make style

* Add suggestions from code review
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make style, make quality

* Add suggestions from code review
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Add suggestions from code review

Remove MobileViTv2ImageProcessor
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make style

* Add suggestions from code review

Rename MobileViTv2 -> MobileViTV2
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Add suggestions from code review
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update modeling_mobilevitv2.py

make style

* Update serialization.mdx

* Update modeling_mobilevitv2.py

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

* Commit the automatically generated code

using add-new-model-like

* Update description at swiftformer.mdx file

* remove autogenerated code for MaskedImageModeling

* update weight conversion scripts

* Update modeling_swiftformer.py

* update configuration_swiftformer.py

* Update test_modeling_swiftformer.py

* update modeling code - remove einops dependency

* Update _toctree.yml

* update modeling code - remove copied from comments

* update docs

* Revert "update docs"

This reverts commit c2e05e2998fe2cd6eaee8b8cc31aca5222bac9fb.

* update docs

* remove unused reference SwiftFormerImageProcessor

* update dependency_versions_table.py

* update swiftformer.mdx

* update swiftformer.mdx

* change model output type - no attentions

* update model org name

* Fix typo

* fix copies

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

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

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

* Update docs/source/en/model_doc/swiftformer.mdx
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

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

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

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

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

* Update modeling_swiftformer.py

fix-copies

* make style, make quality, fix-copies

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

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

* make style
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Add suggestions from code review
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Add suggestions from code review
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make fix-copies

* Update modeling_swiftformer.py

* Update modeling_swiftformer.py

* Add suggestions from code review
Co-Authored-By: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* Update feature selection

* Check compatibility with datasets version

* Checkout from datasets main

Adds FocalNet by Microsoft to transformers

---------
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: alaradirik <alaradirik@gmail.com>

* Add ConvNeXt V2 to transformers
* TF model is separated from the PR to fix issues

* Add EfficientNet to transformers

* initial commit. added tip placeholders and a script

* removed unused imports, fixed paths

* fixed generated links

* make style

* split language modeling doc into two: causal language modeling and masked language modeling

* added check_task_guides.py to make fix-copies

* review feedback addressed

* Added TF example for image classification

* Code style polishing

* code style polishing

* minor polishing

* fixed a link in a tip, and a typo in the inference TF content

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

* Update docs/source/en/tasks/image_classification.mdx
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* review feedback addressed

* make style

* added PushToHubCallback with save_strategy="no"

* minor polishing

* added PushToHubCallback with save_strategy=no

* minor polishing

* Update docs/source/en/tasks/image_classification.mdx

* added data augmentation
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make style
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update doc example feature extractor -> image processor

* Apply suggestions from code review

* 📝 start adding inference section to task guides

* ✨ make style

* 📝 add multiple choice

* add rest of inference sections

* make style

* add compute_metric, push_to_hub, pipeline

* make style

* add updated sequence and token classification

* make style

* make edits in token classification

* add audio classification

* make style

* add asr

* make style

* add image classification

* make style

* add summarization

* make style

* add translation

* make style

* add multiple choice

* add language modeling

* add qa

* make style

* review and edits

* apply reviews

* make style

* fix call to processor

* apply audio reviews

* update to better asr model

* make style

* Add CLIP image processor

* Crop size as dict too

* Update warning

* Actually use logger this time

* Normalize doesn't change dtype of input

* Add perceiver image processor

* Tidy up

* Add DPT image processor

* Add Vilt image processor

* Tidy up

* Add poolformer image processor

* Tidy up

* Add LayoutLM v2 and v3 imsge processors

* Tidy up

* Add Flava image processor

* Tidy up

* Add deit image processor

* Tidy up

* Add ConvNext image processor

* Tidy up

* Add levit image processor

* Add segformer image processor

* Add in post processing

* Fix up

* Add ImageGPT image processor

* Fixup

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Add VideoMAE image processor

* Tidy up

* Add ImageGPT image processor

* Fixup

* Add ViT image processor

* Tidy up

* Add beit image processor

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Fix up

* Fix flava and remove tree module

* Fix image classification pipeline failing tests

* Update feature extractor in trainer scripts

* Update pad_if_smaller to accept tuple and int size

* Update for image segmentation pipeline

* Update src/transformers/models/perceiver/image_processing_perceiver.py
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

* Update src/transformers/image_processing_utils.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/beit/image_processing_beit.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* PR comments - docstrings; remove accidentally added resize; var names

* Update docstrings

* Add exception if size is not in the right format

* Fix exception check

* Fix up

* Use shortest_edge in tuple in script
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Link to the Datasets doc

* Remove unwanted file

* Reorganize doc for multilingual support

* Fix style

* Style

* Toc trees

* Adapt templates

* ✨ refactor code samples with framework-specific blocks

* ✨ update training.mdx

* 🖍 apply feedback

* 🖍 fix links in guides

* 🖍 apply feedback

* 📝 first draft of audio/vision guides

* ✨ make fixup

* 🖍 fix typo

* 🖍 close parentheses

* 🖍 apply feedback

* 🖍 apply feedback, make fixup

* 🖍 more fixup for perceiver

* 🖍 apply feedback

* ✨ make fixup

* 🖍 fix data collator