GitLab

* Honor existing attention mask in tokenzier.pad

* Fix initialization of attention mask

* Roll the implem on all subclasses

* Fix tests

* up

* Update src/transformers/generation_stopping_criteria.py

* finish

* Adding support for tokens being suffixes or part of each other.

* Better test name.

* Implement img seg pipeline

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

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

* Update output shape with individual masks

* Rm dev change

* Remove loops in test
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix issues with LED model

* Style pass

* Bugfixes

* correct attentions as well
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* up

* overwrite hubert

Fixes #13846

Co-authored-by: Pierre Snell <pierre.snell@botpress.com>
Co-authored-by: Pierre Snell <pierre.snell@botpress.com>

* Tmp.

* Fixing BC for question answering with long context.

* Capping model_max_length to avoid tf overflow.

* Bad workaround bugged roberta.

* Fixing name.

* Allow dataset to be an optional argument for (Distributed)LengthGroupedSampler

* Fix

* Symbolic trace dynamic axes support for BERT like models (albert, bert, distilbert, mobilebert, electra, megatron-bert)
* Sanity checks before tracing that make sure the model to trace is supported
* Adapted to PyTorch 1.9
Co-authored-by: Michael Benayoun <michael@huggingface.co>

* Fixing empty prompts for text-generation when BOS exists.

* Fixing odd case with Pegasus.

* Fixing Bert is Assertion Error.

* update no_* argument

Changes the order so that the no_* argument is created after the original argument AND sets the default for this no_* argument to False

* import copy

* update test

* make style

* Use kwargs to set default=False

* make style

* Add layer-wise scaling

* Add reorder & upcasting argument

* Add OpenAI GPT-2 weight initialization scheme

* start `layer_idx` count at zero for consistency

* disentangle attn and reordered and upscaled attn function

* rename `scale_attn_by_layer` to `scale_attn_by_layer_id`

* make autocast from amp compatible with pytorch<1.6

* fix docstring

* style fixes

* Add fixes from PR feedback, style tweaks

* Fix doc whitespace

* Reformat

* First pass scale_attn_by_layer_idx and reorder_and_upcast_attn tests

* Rename scale_attn_by_layer_idx, add tip

* Remove extra newline

* add test for weight initialization

* update code format

* add assert check weights are fp32

* remove assert

* Fix incorrect merge

* Fix shape mismatch in baddbmm

* Add generation test for Mistral flags
Co-authored-by: leandro <leandro.vonwerra@spoud.io>
Co-authored-by: Keshav Santhanam <keshav2@stanford.edu>
Co-authored-by: J38 <jebolton@stanford.edu>

* update

* add to docs and init

* make fix-copies

* Fix length of IterableDatasetShard and add test

* Add comments

* Enable readme link synchronization

* Style

* Reuse regex pattern

* Apply suggestions

* Update

Fixes #13697

* add sigopt hpo to transformers.
Signed-off-by: Ding, Ke <ke.ding@intel.com>

* extend sigopt changes to test code and others..
Signed-off-by: Ding, Ke <ke.ding@intel.com>

* Style.

* fix style for sigopt integration.
Signed-off-by: Ding, Ke <ke.ding@intel.com>

* Add necessary information to run unittests on SigOpt.
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Use fp16 checkpoints

* Style

* Fix outputs and disable OOM tests

* Correct another output

* Use a random smaller model for generation tests

* repo quickfix

* fix gradient checkpointing

* Make gradient_checkpointing a training argument

* Update src/transformers/modeling_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Update src/transformers/configuration_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Fix tests

* Style

* document Gradient Checkpointing as a performance feature

* Small rename

* PoC for not using the config

* Adapt BC to new PoC

* Forgot to save

* Rollout changes to all other models

* Fix typo
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* Force dtype, add tests

* Local torch imports

* Remove unused logic (always ndarray)

* up

* up

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* cleanup

* Removed regression/ folder

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* cleanup

* Fixed import error

* Remove unnecessary import statements

* Changed max_2d_positions from class variable to instance variable of the config class

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* cleanup

* Add support for exporting PyTorch LayoutLM to ONNX

* cleanup

* Fixed import error

* Changed max_2d_positions from class variable to instance variable of the config class

* Use super class generate_dummy_inputs method
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Add support for Masked LM, sequence classification and token classification
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Removed uncessary import and method

* Fixed code styling

* Raise error if PyTorch is not installed

* Remove unnecessary import statement
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Test np padding

* Pass feature extraction tests

* Update type hints

* Fix flaky integration tests

* Try a more stable waveform

* Add to_numpy jax support

* int32 attention masks

* Refactor normalization tests

* beit-flax

* updated FLAX_BEIT_MLM_DOCSTRING

* removed bool_masked_pos from classification

* updated Copyright

* code refactoring: x -> embeddings

* updated test: rm from_pt

* Update docs/source/model_doc/beit.rst

* model code dtype updates and
other changes according to review

* relative_position_bias
revert back to pytorch design

* upload

* correct

* correct

* correct

* finish

* up

* up

* up again

* Dynamic model

* Use defensive flag

* Style

* Doc and arg rename

* Arg rename

* Add tests

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Address review comments

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Init FNet

* Update config

* Fix config

* Update model classes

* Update tokenizers to use sentencepiece

* Fix errors in model

* Fix defaults in config

* Remove position embedding type completely

* Fix typo and take only real numbers

* Fix type vocab size in configuration

* Add projection layer to embeddings

* Fix position ids bug in embeddings

* Add minor changes

* Add conversion script and remove CausalLM vestiges

* Fix conversion script

* Fix conversion script

* Remove CausalLM Test

* Update checkpoint names to dummy checkpoints

* Add tokenizer mapping

* Fix modeling file and corresponding tests

* Add tokenization test file

* Add PreTraining model test

* Make style and quality

* Make tokenization base tests work

* Update docs

* Add FastTokenizer tests

* Fix fast tokenizer special tokens

* Fix style and quality

* Remove load_tf_weights vestiges

* Add FNet to  main README

* Fix configuration example indentation

* Comment tokenization slow test

* Fix style

* Add changes from review

* Fix style

* Remove bos and eos tokens from tokenizers

* Add tokenizer slow test, TPU transforms, NSP

* Add scipy check

* Add scipy availabilty check to test

* Fix tokenizer and use correct inputs

* Remove remaining TODOs

* Fix tests

* Fix tests

* Comment Fourier Test

* Uncomment Fourier Test

* Change to google checkpoint

* Add changes from review

* Fix activation function

* Fix model integration test

* Add more integration tests

* Add comparison steps to MLM integration test

* Fix style

* Add masked tokenization fix

* Improve mask tokenization fix

* Fix index docs

* Add changes from review

* Fix issue

* Fix failing import in test

* some more fixes

* correct fast tokenizer

* finalize

* make style

* Remove additional tokenization logic

* Set do_lower_case to False

* Allow keeping accents

* Fix tokenization test

* Fix FNet Tokenizer Fast

* fix tests

* make style

* Add tips to FNet docs
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>