GitLab

* deduplication draft

* update style

* update style test

* dummy test main

* rename modules

* rename functions

* return extremes in deduplicate_clusters

* update style

* cast str for gzip

* update doc string

* time processing

* use dataset map to compute minhash

* fill value for short token

* remove da map method

* update style

* use share object to multiprocess

* update style

* use f-string and minor fix
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* update style

* use module parameters

* change ds_dedup to ds_filter

* save ds_dedup

* mv test to script tests

* make jaccard threshold a parameter of deduplicate_dataset

* update style

* add doc strings

* update style

* add doc string for DuplicationIndex

* save files into data dir

* update readme

* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* make near deduplication optional

* move near deduplication in README

* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>

* use f string
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* add onnx support for debertav2

* debertav2 -> deberta-v2 in onnx features file

* remove causal lm

* add deberta-v2-xlarge to onnx tests

* use self.type().dtype() in xsoftmax
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* remove hack for deberta

* remove unused imports

* Update src/transformers/models/deberta_v2/configuration_deberta_v2.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* use generate dummy inputs

* linter

* add imports

* add support for deberta v1 as well

* deberta does not support multiple choice

* Update src/transformers/models/deberta/configuration_deberta.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* Update src/transformers/models/deberta_v2/configuration_deberta_v2.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* one line ordered dict

* fire bu...

* Add UL2
Co-authored-by: Daniel Hesslow <Daniel.Hesslow@gmail.com>

* Correct naming

* sort better

* up

* apply sylvains suggestion

On line 180, `torch.tensor(-1.0, xxx)` gives the error "TypeError: 'float' object cannot be interpreted as an integer" 
This is because the dtype here is `int64`.  For `dtype=int64`, this needs to simply be `-1`.  
This impacts the long-t5-tglogbal-x model.  It does not impact the long-t5-local-x version which does not appear to call this line.

* Use torch.finfo(self.dtype).min

* for GPTNeoX

* for Albert

* For Splinter

* Update src/transformers/models/data2vec/modeling_data2vec_audio.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix -inf used in Bart-like models

* Fix a few remaining -inf

* more fix

* clean up

* For CLIP

* For FSMT

* clean up

* fix test

* Add dtype argument and use it for LayoutLMv3

* update FlaxLongT5Attention
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix cache for GPT-Neo-X

* Add more tests

* deprecate is_torch_bf16_available

* address suggestions

* Also propagate changes to blenderbot, blenderbot_small, marian, mbart, and pegasus

* Use workflow_run event for push CI

* change to workflow_run

* Add comments
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Added translation of installation.mdx to Portuguese, as well
as default templates of _toctree.yml and _config.py

* [ build_documentation.yml ] - Updated doc_builder to build
documentation in Portuguese.
[ pipeline_tutorial.mdx ] - Created translation for the pipeline_tutorial.mdx.

* [ build_pr_documentation.yml ] - Added pt language to pr_documentation builder.

[ pipeline_tutorial.mdx ] - Grammar changes.

* [ accelerate.mdx ] - Translated to Portuguese the acceleration tutorial.

* [ multilingual.mdx ] - Added portuguese translation for multilingual tutorial.

[ training.mdx ] - Added portuguese translation for training tutorial.

* [ preprocessing.mdx ] - WIP

* Update _toctree.yml

* Adding Pré-processamento to _toctree.yml

* Update accelerate.mdx

* Nits and eliminate preprocessing file while it is ready

* [ index.mdx ] - Translated to Portuguese the index apresentation page.

* [ docs/source/pt ] - Updated _toctree.yml to match newest translations.

* Fix build_pr_documentation.yml

* Fix index nits

* nits in _toctree
Co-authored-by: Omar U. Espejel <espejelomar@gmail.com>

* Fix eval to compute rouge correctly for rouge_score

* styling

* moving sentence tokenization to utils from run_eval

* saving ckpt in mlflow

* use existing format of args

* fix documentation
Co-authored-by: Swetha Mandava <smandava@nvidia.com>

* Migrate HFDeepSpeedConfig from trfrs to accelerate

* add `accelerate` to testing dep

* addressing comments

* addressing comments

Using `_shared_state` and avoiding object creation. This is necessary as `notebook_launcher` in `launcers.py` checks `len(AcceleratorState._shared_state)>0` to throw an error.

* resolving comments

1. Use simple API from accelerate to manage the deepspeed config integration
2. Update the related documentation

* reverting changes and addressing comments

* docstring correction

* addressing nits

* addressing nits

* addressing nits 3

* bumping up the accelerate version to 0.10.0

* resolving import

* update setup.py to include deepspeed dependencies

* Update dependency_versions_table.py

* fixing imports

* reverting changes to CI dependencies for "run_tests_pipelines_tf*" tests

These changes didn't help with resolving the failures and I believe this needs to be addressed in another PR.

* removing `accelera...

Bumps [notebook](http://jupyter.org

) from 6.4.10 to 6.4.12.

---
updated-dependencies:
- dependency-name: notebook
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

Bumps [notebook](http://jupyter.org

) from 6.4.10 to 6.4.12.

---
updated-dependencies:
- dependency-name: notebook
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* nightly build pytorch CI

* fix working dir

* change time and event name
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Refine BF16 check in CPU/GPU

* Fixes

* Renames

* fix the naming

* from pt in test for now

* make style

* slow test and removed from_pt

VIsualBert uses bert-base-uncased tokenizer, therefore, instead of {mask}, the mask token should be [MASK]

* Add flag to push weights directly into main

This reverts commit b76290f4.

* [Wav2Vec2Conformer] Official release

* remove from not-in-readme

* rembert: fix python codeblock

* rembert: use correct google/rembert checkpoint name in documentation

* rembert: use correct google/rembert checkpoint name in TF documentation

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Function refactor

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

* add new bloom classes

* (feat) add bloom classification tests; make style

* style: change import in test

* add some typehints to bloom classes

* merge main into branch

* fix: input checking in bloom seq classification

* fix tests

* change model class tests

* fix few tests

- more tests should pass
- one test left

* make token classifier return hidden states

* style: make BLOOM typehints consistent
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Swin models call TFSwinMainLayer

* Tidy up

* Add note on amy's contribution.
Co-authored-by: Amy Roberts <aeroberts4444@gmail.com>

* remove non-tech comment.

Co-authored by: Amy Roberts <aeroberts4444@gmail.com>
Co-authored-by: Amy Roberts <aeroberts4444@gmail.com>

* check

* update the RAG-end2end with new PL and RAY

* removed unwanted comments

* add jit mode option and model wrap

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

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

* refine code

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

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

* add ut and refine code

* code refine

* refine code

* add inference doc

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

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

* add cpu inference performance doc

* Update perf_infer_cpu.mdx

* Update perf_infer_cpu.mdx

* Update performance.mdx

* Update _toctree.yml

* refine jit func naming

* Update _toctree.yml

* Delete perf_infer_gpu_one.mdx

* Update perf_infer_cpu.mdx

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

* add none check before jit

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

* Update docs/source/en/perf_infer_cpu.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Fix doc builder Dockerfile
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Initial commit

* Make some fixes

* Make PT model full forward pass

* Drop TF & Flax implementation, fix copies etc

* Add Flax model and update some corresponding stuff

* Drop some TF things

* Update config and flax local attn

* Add encoder_attention_type to config

* .

* Update docs

* Do some cleansing

* Fix some issues -> make style; add some docs

* Fix position_bias + mask addition + Update tests

* Fix repo consistency

* Fix model consistency by removing flax operation over attn_mask

* [WIP] Add PT TGlobal LongT5

* .

* [WIP] Add flax tglobal model

* [WIP] Update flax model to use the right attention type in the encoder

* Fix flax tglobal model forward pass

* Make the use of global_relative_attention_bias

* Add test suites for TGlobal model

* Fix minor bugs, clean code

* Fix pt-flax equivalence though not convinced with correctness

* Fix LocalAttn implementation to match the original impl. + update README...