GitLab

* Add multi-node conditions in trainer_qa.py and trainer_seq2seq.py

* Code improvement

Fix link typo of the following content.
PyTorch version, Trainer
PyTorch version, no Trainer

* edit: casting attention_mask to long in DataCollatorCTCWithPadding

* edit: casting attention_mask to long in DataCollatorCTCWithPadding

The link to https://github.com/vasudevgupta7/bigbird is vulnerable to repojacking (it redirects to the orignial project that changed name), you should change the link to the current name of the project. if you won't change the link, an attacker can open the linked repository and attacks users that trust your links

Bumps [joblib](https://github.com/joblib/joblib) from 0.16.0 to 1.2.0.
- [Release notes](https://github.com/joblib/joblib/releases)
- [Changelog](https://github.com/joblib/joblib/blob/master/CHANGES.rst)
- [Commits](https://github.com/joblib/joblib/compare/0.16.0...1.2.0

)

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

Bumps [joblib](https://github.com/joblib/joblib) from 1.1.0 to 1.2.0.
- [Release notes](https://github.com/joblib/joblib/releases)
- [Changelog](https://github.com/joblib/joblib/blob/master/CHANGES.rst)
- [Commits](https://github.com/joblib/joblib/compare/1.1.0...1.2.0

)

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

Bumps [joblib](https://github.com/joblib/joblib) from 0.16.0 to 1.2.0.
- [Release notes](https://github.com/joblib/joblib/releases)
- [Changelog](https://github.com/joblib/joblib/blob/master/CHANGES.rst)
- [Commits](https://github.com/joblib/joblib/compare/0.16.0...1.2.0

)

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

* Update no_trainer script for summarization

* removed unnecessary import

* fixes notation mistake

* removed: unused variable

* fix args option

* fix trainer eval log

* fix out of memory qa script

* do isort, black, flake

* fix tokenize target

* take it back.

* fix: comment

* add wav2vec2_alignment

* Update alignment.py

* Update examples/research_projects/wav2vec2/alignment.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update examples/research_projects/wav2vec2/alignment.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update examples/research_projects/wav2vec2/alignment.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update examples/research_projects/wav2vec2/alignment.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update README.md

* fix style

* fix imports

* fix multithread

* fix bash script

* [@anton-l] Style fixes and docstrings

* [@anton-l] Style fixes and docstrings

* Update alignment.py

fix blank id in backtrack
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: anton-l <aglozhkov@gmail.com>

* Use repo_type instead of deprecated datasets repo IDs

* Add missing one in doc

Bumps [protobuf](https://github.com/protocolbuffers/protobuf) from 3.19.4 to 3.19.5.
- [Release notes](https://github.com/protocolbuffers/protobuf/releases)
- [Changelog](https://github.com/protocolbuffers/protobuf/blob/main/generate_changelog.py)
- [Commits](https://github.com/protocolbuffers/protobuf/compare/v3.19.4...v3.19.5

)

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

The overwrite_cache parameter is declared twice.

Bumps [oauthlib](https://github.com/oauthlib/oauthlib) from 3.2.0 to 3.2.1.
- [Release notes](https://github.com/oauthlib/oauthlib/releases)
- [Changelog](https://github.com/oauthlib/oauthlib/blob/master/CHANGELOG.rst)
- [Commits](https://github.com/oauthlib/oauthlib/compare/v3.2.0...v3.2.1

)

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

* Fix: update ltp word segmentation call in mlm_wwm

* Fix: update ltp word segmentation call in mlm_wwm

* Fix: update ltp word segmentation call in mlm_wwm

Bumps [mako](https://github.com/sqlalchemy/mako) from 1.2.0 to 1.2.2.
- [Release notes](https://github.com/sqlalchemy/mako/releases)
- [Changelog](https://github.com/sqlalchemy/mako/blob/main/CHANGES)
- [Commits](https://github.com/sqlalchemy/mako/commits

)

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

* fixed bug which caused overwrite_cache to always be True (#18967).

* reformatting changes

* NeptuneCallback improvements

* After review suggestions and deduplication of initial run

* Added volatile checkpoints support due to missing post-rebase commit

* Update README per review comments

- Remove list formatting
- Correct Neptune docs link
Co-authored-by: Sabine <sabine.nyholm@neptune.ai>

* [JAX] Replace all jax.tree_* calls with jax.tree_util.tree_*

* fix double tree_util

* add accelerator.end_training()

Some trackers need this to end their runs.

* fixup and quality

* add space

* add space again ?!?

Co-authored-by: Arun Rajaram <arunrajaram@Aruns-MacBook-Pro.local>

* fixed incorrect param to hasattr

* simplified condition checks

* code cleanup

Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 6.3.0 to 6.5.1.
- [Release notes](https://github.com/jupyter/nbconvert/releases)
- [Commits](https://github.com/jupyter/nbconvert/compare/6.3.0...6.5.1

)

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

Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 6.3.0 to 6.5.1.
- [Release notes](https://github.com/jupyter/nbconvert/releases)
- [Commits](https://github.com/jupyter/nbconvert/compare/6.3.0...6.5.1

)

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

* `model.tie_weights()` should be applied after `accelerator.prepare`

Weight tying should be done after the model has been moved to XLA device as mentioned on PyTorch/XLA Troubleshooting guide [here](https://github.com/pytorch/xla/blob/master/TROUBLESHOOTING.md#xla-tensor-quirks)

* format code

* add examples subfolder

* mention examples in codeparrot readme

* use Trainer optimizer and scheduler type and add output_dir as argument

* add example of text-to-python and python-to-text models

* mention the downstream examples in the readme

* fix typo

* examples: add Bloom support for token classification (FLAX, PyTorch and TensorFlow)

* examples: remove support for Bloom in token classication (FLAX and TensorFlow currently have no support for it)

* Update run_translation_no_trainer.py

found an error in selecting `no_decay` parameters and some small modifications when the user continues to train from a checkpoint

* fixs `no_decay` and `resume_step` issue

1. change `no_decay` list
2. if use continue to train their model from provided checkpoint, the `resume_step` will not be initialized properly if `args.gradient_accumulation_steps != 1`