GitLab

* Add first draft

* Make model importable

* Make SwinForMaskedImageModeling importable

* Fix imports

* Add missing inits

* Add support for Swin

* Fix bug

* Fix bug

* Fix another bug

* Fix Swin MIM implementation

* Fix default encoder stride

* Fix Swin

* Add print statements for debugging

* Add image_size data argument

* Fix Swin

* Fix image_size

* Add print statements for debugging

* Fix print statement

* Remove print statements

* Improve reshaping of bool_masked_pos

* Add support for DeiT, fix tests

* Improve docstrings

* Apply new black version

* Improve script

* Fix bug

* Improve README

* Apply suggestions from code review

* Remove DS_Store and add to gitignore

* Apply suggestions from code review + fix BEiT Flax

* Revert BEiT changes

* Improve README

* Fix code quality

* Improve README
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* fix README

* fix more arxiv links

* make fix-copies
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Added all files, PoolFormerFeatureExtractor still failing tests

* Fixed PoolFormerFeatureExtractor not being able to import

* Completed Poolformer doc

* Applied Suggested fixes

* Fixed errors in modeling_auto.py

* Fix feature extractor, convert docs to Markdown, styling of code

* Remove PoolFormer from check_repo and fix integration test

* Remove Poolformer from check_repo

* Fixed configuration_poolformer.py docs and removed inference.py from poolformer

* Ran with black v22

* Added PoolFormer to _toctree.yml

* Updated poolformer doc

* Applied suggested fixes and added on README.md

* Did make fixup and make fix-copies, tests should pass now

* Changed PoolFormer weights conversion script name and fixed README

* Applied fixes in test_modeling_poolformer.py and modeling_poolformer.py

* Added PoolFormerFeatureExtractor to AutoFeatureExtractor API
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

* logger

* Update docs/source/main_classes/logging.mdx
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Update docs/source/main_classes/logging.mdx
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* [t5] faster/leaner custom layer norm

* wip

* apex.normalization.FusedRMSNorm

* cleanup

* cleanup

* add doc

* add catch all

* Trigger CI

* expand

* TF generate start refactor

* Add tf tests for sample generate

* re-organize

* boom boom

* Apply suggestions from code review

* re-add

* add all code

* make random greedy pass

* make encoder-decoder random work

* further improvements

* delete bogus file

* make gpt2 and t5 tests work

* finish logits tests

* correct logits processors

* correct past / encoder_outputs drama

* refactor some methods

* another fix

* refactor shape_list

* fix more shape list

* import shape
_list

* finish docs

* fix imports

* make style

* correct tf utils

* Fix TFRag as well

* Apply Lysandre's and Sylvais suggestions

* Update tests/test_generation_tf_logits_process.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Update src/transformers/tf_utils.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* remove cpu according to gante

* correct logit processor
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Re-export `KeyDataset`.

* Update the docs locations.

* add a network debug script and document it

* doc

* Add doctesting section

* Improve

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Forward looks for inputs, not input_ids

This reverts commit 41168a49.

* Add attribute_map

* Add mention in docs

* Set hidden_size attribute correctly

* Add note about Transformer-based models only
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

"to make ensure" is redundant.

* [deepspeed docs] round_robin_gradients

* training and/or eval/predict loss is

* Update docs/source/main_classes/deepspeed.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add local and TensorFlow ONNX export examples to docs

* Use PyTorch - TensorFlow split

* Add TensorFlow support for ONNX export

* Change documentation to mention conversion with Tensorflow

* Refactor export into export_pytorch and export_tensorflow

* Check model's type instead of framework installation to choose between TF and Pytorch
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Alberto Bégué <alberto.begue@della.ai>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Expand tutorial for custom models

* Style

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

* [trainer docs] document how to select specific gpus

* expand

* add urls

* add accelerate launcher

* added classes to get started with constrained beam search

* in progress, think i can directly force tokens now but not yet with the round robin

* think now i have total control, now need to code the bank selection

* technically works as desired, need to optimize and fix design choices leading to undersirable outputs

* complete PR #1 without disjunctive decoding

* removed incorrect tests

* Delete k.txt

* Delete test.py

* Delete test.sh

* revert changes to test scripts

* genutils

* full implementation with testing, no disjunctive yet

* shifted docs

* passing all tests realistically ran locally

* removing accidentally included print statements

* fixed source of error in initial PR test

* fixing the get_device() vs device trap

* fixed documentation docstrings about constrained_beam_search

* fixed tests having failing for Speech2TextModel's floating point inputs

* fix cuda long tensor

* added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search

* deleted accidentally added test halting code with assert False

* code reformat

* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/test_generation_utils.py

* fixing based on comments on PR

* took out the testing code that should but work fails without the beam search moditification ; style changes

* fixing comments issues

* docstrings for ConstraintListState

* typo in PhrsalConstraint docstring

* docstrings improvements
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add model scaling section

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* integrate reviewer feedback

* initialize GPU properly

* add note about BnB optimizer

* move doc from `scaling.mdx` to `performance.mdx`

* integrate reviewer feedback

* revert section levels
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* PoC for a ProcessorMixin class

* Documentation

* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Roll out to other processors

* Add base feature extractor class in init

* Use args and kwargs
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add wrapper classes

* convert inner layers to tf

* Add TF Encoder and Decoder layers

* TFSpeech2Text models

* Loadable model

* TF model with same outputs as PT model

* test skeleton

* correct tests and run the fixup

* correct attention expansion

* TFSpeech2Text pask_key_values with TF format

* electra is added to onnx supported model

* add google/electra-base-generator for test onnx module
Co-authored-by: Lewis Tunstall <lewis.c.tunstall@gmail.com>

* 📝 add config section

* 📝 finish first draft

* 📝 add feature extractor and processor

* 🖍 apply feedback from review

* 📝 minor edits

* last review

* First draft

* Add conversion script

* Improve conversion script

* Improve docs and implement tests

* Define model output class

* Fix tests

* Fix more tests

* Add model to README

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply more suggestions from code review

* Apply suggestions from code review

* Rename dims to hidden_sizes

* Fix equivalence test

* Rename gamma to gamma_parameter

* Clean up conversion script

* Add ConvNextFeatureExtractor

* Add corresponding tests

* Implement feature extractor correctly

* Make implementation cleaner

* Add ConvNextStem class

* Improve design

* Update design to also include encoder

* Fix gamma parameter

* Use sample docstrings

* Finish conversion, add center cropping

* Replace nielsr by facebook, make feature extractor tests smaller

* Fix integration test
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* [deepspeed docs] DeepSpeed ZeRO Inference

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* tweak

* deal with black

* extra cleanup, better comments
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Standardize instance segmentation models outputs

* Rename output

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

* Add legacy argument to the config and model forward

* Update src/transformers/models/beit/modeling_beit.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Copy fix in Segformer
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Allow dynamic modules to use relative imports

* Work for configs

* Fix last merge conflict

* Save code of registered custom objects

* Map strings to strings

* Fix test

* Add tokenizer

* Rework tests

* Tests

* Ignore fixtures py files for tests

* Tokenizer test + fix collection

* With full path

* Rework integration

* Fix typo

* Remove changes in conftest

* Test for tokenizers

* Add documentation

* Update docs/source/custom_models.mdx
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add file structure and file content

* Add more doc

* Style

* Update docs/source/custom_models.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Address review comments
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* first draft of pipeline, autoclass, preprocess tutorials

* apply review feedback

* 🖍 apply feedback from patrick/niels

* 📝add output image to preprocessed image

* 🖍 apply feedback from patrick

* add fine-tune tutorial

* make edits, fix style

* 📝 make edits

* 🖍 fix code format links to external libraries

* 🔄revert code formatting

* 🖍 use DefaultDataCollator instead of DataCollatorWithPadding

* [deepspeed doc] fix import, extra notes

* typo