GitLab

* 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>

* Fix special tokens not correctly tokenized

* Add testing

* Fix

* Fix

* Use user workflows instead of directly assigning variables

* Enable test of fast tokenizers

* Update test of canine tokenizer

* finish

* add test

* push

* remove unnecessary code

* up

* correct test

* Update src/transformers/training_args.py

* made tokenizer fully picklable

* remove whitespace

* added testcase

* correct

* add tests

* Update src/transformers/feature_extraction_sequence_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* finish

* delete bogus file

* correct some stuff

* finish

* finish

* added initial files

* fixes pipeline

* fixes style and quality

* fixes doc issue and positional encoding

* fixes layer norm and test

* fixes quality issue

* fixes code quality

* removed extra layer norm

* added layer norm back in encoder and decoder

* added more code copy quality checks

* update tests

* Apply suggestions from code review

* fix import

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

* Push to hub when saving checkpoints

* Add model card

* Revert partial model card

* Small fix for checkpoint

* Add tests

* Add documentation

* Fix tests

* Bump huggingface_hub

* Fix test

apparently).

* simplify local attention

* update tests

* add a comment and use torch.bitwise_xor

* finalize

* Apply suggestions from code review

* finish cleaner implementation

* more tests

* small fix

* finish

* up

* Enabling dataset iteration on pipelines.

Enabling dataset iteration on pipelines.

Unifying parameters under `set_parameters` function.

Small fix.

Last fixes after rebase

Remove print.

Fixing text2text `generate_kwargs`

No more `self.max_length`.

Fixing tf only conversational.

Consistency in start/stop index over TF/PT.

Speeding up drastically on TF (nasty bug where max_length would increase
a ton.)

Adding test for support for non fast tokenizers.

Fixign GPU usage on zero-shot.

Fix working on Tf.

Update src/transformers/pipelines/base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Update src/transformers/pipelines/base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Small cleanup.

Remove all asserts + simple format.

* Fixing audio-classification for large PR.

* Overly explicity null checking.

* Encapsulating GPU/CPU pytorch manipulation directly within `base.py`.

* Removed internal state for parameters of the  pipeline.

Instead of overriding implicitly internal state, we moved
to real named arguments on every `preprocess`, `_forward`,
`postprocess` function.

Instead `_sanitize_parameters` will be used to split all kwargs
of both __init__ and __call__ into the 3 kinds of named parameters.

* Move import warnings.

* Small fixes.

* Quality.

* Another small fix, using the CI to debug faster.

* Last fixes.

* Last fix.

* Small cleanup of tensor moving.

* is not None.

* Adding a bunch of docs + a iteration test.

* Fixing doc style.

* KeyDataset = None guard.

* RRemoving the Cuda test for pipelines (was testing).

* Even more simple iteration test.

* Correct import .

* Long day.

* Fixes in docs.

* [WIP] migrating object detection.

* Fixed the target_size bug.

* Fixup.

* Bad variable name.

* Fixing `ensure_on_device` respects original ModelOutput.

* Fixing #13381

* Enabling automatic LED models.

* Moving slow tokenizer to the Trie world.

* Adding more docstrings to the Trie.

* Fixing doctest (incompatible wiht our format? )

* Update src/transformers/tokenization_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding a lot more comment into the internals of this algorithm.

* Cleaner doc.

* Fixing the namings.

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

* quality.

* Fixing longest first match.

* Small improvements to cuts + more test + canine resistant test.

* Fixing fast test.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Implement object-detection pipeline

* Define threshold const

* Add `threshold` argument

* Refactor

* Uncomment test inputs

* `rm
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better doc
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Rm unnecessary lines
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better naming
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

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

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

* Fix typo

* Add `detr-tiny` for tests

* Add `ObjectDetectionPipeline` to `trnsfrmrs/init`

* Implement new bbox format

* Update detr post_process

* Update `load_img` method obj det pipeline

* make style

* Implement new testing format for obj det pipeln

* Add guard pytorch specific code in pipeline

* Add doc

* Make pipeline_obj_tet tests deterministic

* Revert some changes to `post_process` COCO api

* Chore

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

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

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

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

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

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

* Rm timm requirement

* make fixup

* Add timm requirement to test

* Make fixup

* Guard torch.Tensor

* Chore

* Delete unnecessary comment
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Complete basic mechanism

* Save

* Complete everything

* Style & Quality

* Update READMEs

* Add testing

* Fix README.md format

* Apply suggestions

* Fix format

* Update utils/check_copies.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix logit_scale init

* add logit_scale_init_value as config param

* ✅ Update image-classification example's tests

* 🔥 remove cats_and_dogs test samples

* 💄 fix flake8

* refactor GPT Config to allow dyn. properties

* make attribute_map a class attribute

* remove old code

* update unit test to test config: Add test for common properties setter

* update unit test to test config: Add test for common properties passed as parameters to __init__

* update to black code format

* Allow that setters are not defined for certain config classes

* update config classes to implement attribute_map

* bugfix lxmert config - id2labels was not defined when num_labels was set

* update broken configs - add attribute_maps

* update bart config

* update black codestyle

* update documentation on common config attributes

* update GPTJ config to new attribute map

* update docs on common attributes

* gptj config: add max_position_embeddings

* gptj config: format with black

* update speech to text 2 config

* format doc file to max_len 119

* update config template

* Adding a test for multibytes unicode.

* Adding some accents.

* Making sure decoding works.

* Make tests passing by being cheesy.