GitLab

* add test in trainer and test tokenizer saving wi
th trainer

* quality

* reverse trainer changes

* replace test in test_trainer by a test for all the tokenizers

* format

* add can_save_slow_tokenizer attribute to all tokenizers

* fix Herbert

* format

* Change comment in error

* add comments and a new assert

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

* change ValueError barthez

* change ValueError BigBird

* change ValueError Camembert

* change ValueError Mbart50

* change ValueError Pegasus

* change ValueError ReFormer

* change ValueError T5

* change ValueError RoBERTa

* XLNET fast

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

* change `assert` into `self.assertIn`

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

* fix_torch_device_generate_test

* remove @

* up

* correct some bugs

* correct model

* finish speech2text extension

* up

* up

* up

* up

* Update utils/custom_init_isort.py

* up

* up

* update with tokenizer

* correct old tok

* correct old tok

* fix bug

* up

* up

* add more tests

* up

* fix docs

* up

* fix some more tests

* add better config

* correct some more things
"

* fix tests

* improve docs

* Apply suggestions from code review

* Apply suggestions from code review

* final fixes

* finalize

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

* apply suggestions Lysandre and Sylvain

* apply nicos suggestions

* upload everything

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>
Co-authored-by: your_github_username <your_github_email>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Torchscript test for Flaubert

* Update tests/test_modeling_flaubert.py

* Update tests/test_modeling_flaubert.py

* Torchscript test for ConvBERT

* Apply suggestions from code review

* Torchscript test for DistilBERT

* Update tests/test_modeling_distilbert.py

* Torchscript test

* Remove print statement

* Add the audio classification pipeline

* Remove autoconfig exception

* Mark ffmpeg test as slow

* Rearrange pipeline tests

* Add small test

* Replace asserts with ValueError

* Test GPTJ implementation

* Fixed conflicts

* Update __init__.py

* Update __init__.py

* change GPT_J to GPTJ

* fix missing imports and typos

* use einops for now
(need to change to torch ops later)

* Use torch ops instead of einsum

* remove einops deps

* Update configuration_auto.py

* Added GPT J

* Update gptj.rst

* Update __init__.py

* Update test_modeling_gptj.py

* Added GPT J

* Changed configs to match GPT2 instead of GPT Neo

* Removed non-existent sequence model

* Update configuration_auto.py

* Update configuration_auto.py

* Update configuration_auto.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Progress on updating configs to agree with GPT2

* Update modeling_gptj.py

* num_layers -> n_layer

* layer_norm_eps -> layer_norm_epsilon

* attention_layers -> num_hidden_layers

* Update modeling_gptj.py

* attention_pdrop -> attn_pdrop

* hidden_act -> activation_function

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* fix layernorm and lm_head size
delete attn_type

* Update docs/source/model_doc/gptj.rst
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* removed claim that GPT J uses local attention

* Removed GPTJForSequenceClassification

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

* Removed unsupported boilerplate

* Update tests/test_modeling_gptj.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/transformers/models/gptj/modeling_gptj.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/transformers/models/gptj/modeling_gptj.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

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

* Update tests/test_modeling_gptj.py
Co-authored-by: Eric Hallahan <eric@hallahans.name>

* Update tests/test_modeling_gptj.py
Co-authored-by: Eric Hallahan <eric@hallahans.name>

* Update tests/test_modeling_gptj.py
Co-authored-by: Eric Hallahan <eric@hallahans.name>

* Update src/transformers/models/gptj/modeling_gptj.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update __init__.py

* Update configuration_gptj.py

* Update modeling_gptj.py

* Corrected indentation

* Remove stray backslash

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Update docs to match

* Remove tf loading

* Remove config.jax

* Remove stray `else:` statement

* Remove references to `load_tf_weights_in_gptj`

* Adapt tests to match output from GPT-J 6B

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Default `activation_function` to `gelu_new`

- Specify the approximate formulation of GELU to ensure parity with the default setting of `jax.nn.gelu()`

* Fix part of the config documentation

* Revert "Update configuration_auto.py"

This reverts commit e9860e9c043b6ebf57a0e705044e9ec9ba2263bb.

* Revert "Update configuration_auto.py"

This reverts commit cfaaae4c4dc70f1fbe9abd60fc8bd0b863b8c011.

* Revert "Update configuration_auto.py"

This reverts commit 687788954fd0cfbc567fa1202d56a4ff9271944f.

* Revert "Update configuration_auto.py"

This reverts commit 194d024ea87d4fcef0dcb08e57f52c47511a9fc6.

* Hyphenate GPT-J

* Undid sorting of the models alphabetically

* Reverting previous commit

* fix style and quality issues

* Update docs/source/model_doc/gptj.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

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

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

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

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

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

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

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

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

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

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

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

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

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

* Replaced GPTJ-specific code with generic code

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

* Made the code always use rotary positional encodings

* Update index.rst

* Fix documentation

* Combine attention classes

- Condense all attention operations into `GPTJAttention`
- Replicate GPT-2 and improve code clarity by renaming `GPTJAttention.attn_pdrop` and `GPTJAttention.resid_pdrop` to `GPTJAttention.attn_dropout` and `GPTJAttention.resid_dropout`

* Removed `config.rotary_dim` from tests

* Update test_modeling_gptj.py

* Update test_modeling_gptj.py

* Fix formatting

* Removed depreciated argument `layer_id` to `GPTJAttention`

* Update modeling_gptj.py

* Update modeling_gptj.py

* Fix code quality

* Restore model functionality

* Save `lm_head.weight` in checkpoints

* Fix crashes when loading with reduced precision

* refactor self._attn(...)` and rename layer weights"

* make sure logits are in fp32 for sampling

* improve docs

* Add `GPTJForCausalLM` to `TextGenerationPipeline` whitelist

* Added GPT-J to the README

* Fix doc/readme consistency

* Add rough parallelization support

- Remove unused imports and variables
- Clean up docstrings
- Port experimental parallelization code from GPT-2 into GPT-J

* Clean up loose ends

* Fix index.rst
Co-authored-by: kurumuz <kurumuz1@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Eric Hallahan <eric@hallahans.name>
Co-authored-by: Leo Gao <54557097+leogao2@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: your_github_username <your_github_email>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Adding a TF variant of the DataCollatorForTokenClassification to get feedback

* Added a Numpy variant and a post_init check to fail early if a missing import is found

* Fixed call to Numpy variant

* Added a couple more of the collators

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

* Fixes, style pass, finished DataCollatorForSeqToSeq

* Added all the LanguageModeling DataCollators, except SOP and PermutationLanguageModeling

* Adding DataCollatorForPermutationLanguageModeling

* Style pass

* Add missing `__call__` for PLM

* Remove `post_init` checks for frameworks because the imports inside them were making us fail code quality checks

* Remove unused imports

* First attempt at some TF tests

* A second attempt to make any of those tests actually work

* TF tests, round three

* TF tests, round four

* TF tests, round five

* TF tests, all enabled!

* Style pass

* Merging tests into `test_data_collator.py`

* Merging tests into `test_data_collator.py`

* Fixing up test imports

* Fixing up test imports

* Trying shuffling the conditionals around

* Commenting out non-functional old tests

* Completed all tests for all three frameworks

* Style pass

* Fixed test typo

* Style pass

* Move standard `__call__` method to mixin

* Rearranged imports for `test_data_collator`

* Fix data collator typo "torch" -> "pt"

* Fixed the most embarrassingly obvious bug

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

* Renaming mixin

* Updating docs
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Dalton Walker <dalton_walker@icloud.com>
Co-authored-by: Andrew Romans <andrew.romans@hotmail.com>

* Deberta_v2 tf

* added new line at the end of file, make style

* +V2, typo

* remove never executed branch of code

* rm cmnt and fixed typo in url filter

* cleanup according to review comments

* added #Copied from

* Add GPT2ForTokenClassification

* Fix dropout exception for GPT2 NER

* Remove sequence label in test

* Change TokenClassifierOutput to TokenClassifierOutputWithPast

* Fix for black formatter

* Remove dummy

* Update docs for GPT2ForTokenClassification

* Fix check_inits ci fail

* Update dummy_pt_objects after make fix-copies

* Remove TokenClassifierOutputWithPast

* Fix tuple input issue
Co-authored-by: danielsejong55@gmail.com <danielsejong55@gmail.com>

* Incorporate tests dependencies in tests_fetcher

* Harder modif

* Debug

* Loop through all files

* Last modules

* Remove debug statement

* Use DS callable API to allow hf_scheduler + ds_optimizer

* Preserve backward-compatibility

* Restore backward compatibility

* Tweak arg positioning

* Tweak arg positioning

* bump the required version

* Undo indent

* Update src/transformers/trainer.py

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

* added missing __spec__ to _LazyModule

* test __spec__ is not None after module import

* changed module_spec arg to be optional in _LazyModule

* fix style issue

* added module spec test to test_file_utils

* Fix AutoTokenizer when a tokenizer has no fast version

* Add test

* albert flax

* year -> 2021

* docstring updated for flax

* removed head_mask

* removed from_pt

* removed passing attention_mask to embedding layer

* distilbert-flax

* added missing self

* docs fix

* removed tied kernal extra init

* updated docs

* x -> hidden states

* removed head_mask

* removed from_pt, +FLAX

* updated year

* First commit

* Make style

* Fix dummy objects

* Add Detectron2 config

* Add LayoutLMv2 pooler

* More improvements, add documentation

* More improvements

* Add model tests

* Add clarification regarding image input

* Improve integration test

* Fix bug

* Fix another bug

* Fix another bug

* Fix another bug

* More improvements

* Make more tests pass

* Make more tests pass

* Improve integration test

* Remove gradient checkpointing and add head masking

* Add integration test

* Add LayoutLMv2ForSequenceClassification to the tests

* Add LayoutLMv2ForQuestionAnswering

* More improvements

* More improvements

* Small improvements

* Fix _LazyModule

* Fix fast tokenizer

* Move sync_batch_norm to a separate method

* Replace dummies by requires_backends

* Move calculation of visual bounding boxes to separate method + update README

* Add models to main init

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* More improvements

* Remove is_split_into_words

* More improvements

* Simply tesseract - no use of pandas anymore

* Add LayoutLMv2Processor

* Update is_pytesseract_available

* Fix bugs

* Improve feature extractor

* Fix bug

* Add print statement

* Add truncation of bounding boxes

* Add tests for LayoutLMv2FeatureExtractor and LayoutLMv2Tokenizer

* Improve tokenizer tests

* Make more tokenizer tests pass

* Make more tests pass, add integration tests

* Finish integration tests

* More improvements

* More improvements - update API of the tokenizer

* More improvements

* Remove support for VQA training

* Remove some files

* Improve feature extractor

* Improve documentation and one more tokenizer test

* Make quality and small docs improvements

* Add batched tests for LayoutLMv2Processor, remove fast tokenizer

* Add truncation of labels

* Apply suggestions from code review

* Improve processor tests

* Fix failing tests and add suggestion from code review

* Fix tokenizer test

* Add detectron2 CI job

* Simplify CI job

* Comment out non-detectron2 jobs and specify number of processes

* Add pip install torchvision

* Add durations to see which tests are slow

* Fix tokenizer test and make model tests smaller

* Frist draft

* Use setattr

* Possible fix

* Proposal with configuration

* First draft of fast tokenizer

* More improvements

* Enable fast tokenizer tests

* Make more tests pass

* Make more tests pass

* More improvements

* Addd padding to fast tokenizer

* Mkae more tests pass

* Make more tests pass

* Make all tests pass for fast tokenizer

* Make fast tokenizer support overflowing boxes and labels

* Add support for overflowing_labels to slow tokenizer

* Add support for fast tokenizer to the processor

* Update processor tests for both slow and fast tokenizers

* Add head models to model mappings

* Make style & quality

* Remove Detectron2 config file

* Add configurable option to label all subwords

* Fix test

* Skip visual segment embeddings in test

* Use ResNet-18 backbone in tests instead of ResNet-101

* Proposal

* Re-enable all jobs on CI

* Fix installation of tesseract

* Fix failing test

* Fix index table

* Add LayoutXLM doc page, first draft of code examples

* Improve documentation a lot

* Update expected boxes for Tesseract 4.0.0 beta

* Use offsets to create labels instead of checking if they start with ##

* Update expected boxes for Tesseract 4.1.1

* Fix conflict

* Make variable names cleaner, add docstring, add link to notebooks

* Revert "Fix conflict"

This reverts commit a9b46ce9afe47ebfcfe7b45e6a121d49e74ef2c5.

* Revert to make integration test pass

* Apply suggestions from @LysandreJik's review

* Address @patrickvonplaten's comments

* Remove fixtures DocVQA in favor of dataset on the hub
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* fix_torch_device_generate_test

* remove @

* wav2vec2 pretraining
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* Add hubert classifier + tests

* Add hubert classifier + tests

* Dummies for all classification tests

* Wav2Vec2 classifier + ER test

* Fix hubert integration tests

* Add hubert IC

* Pass tests for all classification tasks on Hubert

* Pass all tests + copies

* Move models to the SUPERB org

* fix_torch_device_generate_test

* remove @

* finish find and replace

* Fixing mbart50 with `return_tensors` argument too.

* Adding mbart50 tokenization tests.

* Moving `zero-shot-classification` pipeline to new testing.

* Cleaning up old mixins.

* Fixing tests
`sshleifer/tiny-distilbert-base-uncased-finetuned-sst-2-english` is
corrupted in PT.

* Adding warning.

* First pass

* Fix docs of bool_masked_pos

* Add integration script

* Fix docstring

* Add integration test for BeitForMaskedImageModeling

* Remove file

* Fix docs

* Moving `translation` pipeline to new testing scheme.

* Update tokenization mbart tests.

* Moving `token-classification` pipeline to new testing.

* Fix tests.

* Moving `text-generation` pipeline to new testing framework.

* Keep check_model_type but log instead of raise Exception.

* warning -> error.

* Moving `summarization` pipeline to new testing format.

* Remove generate_kwargs from __init__ args.

Moving question_answering tests to the new testing scheme. Had to tweak a little some ModelTesterConfig for pipelines. (#13277)

* Moving question_answering tests to the new testing scheme. Had to tweak
a little some ModelTesterConfig for pipelines.

* Removing commented code.

- Enforce `test_small_models_{tf,pt}` methods to exist (enforce checking
actual values in small tests)
- Add support for non RGB image for the pipeline.

* fix tokenizer_class_from_name

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

* add test
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* New test format for conversational.

* Putting back old mixin.

* Re-enabling auto tests with LazyLoading.

* Feature extraction tests.

* Remove feature-extraction.

* Feature extraction with feature_extractor (No pun intended).

* Update check_model_type for fill-mask.

* fix AutoModel.from_pretrained(..., torch_dtype=...)

* fix to_diff_dict

* add better test

* torch is not always available when a model has self.torch_dtype