GitLab

* Add X-MOD to Readme

* Add documentation for X-MOD

* Implement X-MOD

* Fix formatting of X-MOD docs

* Change signature of X-MOD forward methods to use lang_ids

* Minor changes

* Rebase with main and run make fix-copies

* Make suggested changes to docstrings

* Improve code readability
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix code style

* Conversion script: Remove asserts and type annotations

* Remove _TOKENIZER_FOR_DOC

* XMOD -> Xmod

* Update copyright note

* Fix doctests

* Fix docstring

* Add integration test for FillMaskPipeline

* Revert "Add integration test for FillMaskPipeline"

This reverts commit 4381eb3b1d0f5d85785f89caba83928e6efa6d1f.

* Add end-to-end integration test for mask fill

* make style

* Rebase with main and make fix-copies

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Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix stuff related to the causal_mask in CodeGen.

1. Line 613, `_keys_to_ignore_on_load_missing  =  [r"h\.\d+\.attn\.masked_bias", r"h\.\d+\.attn\.bias"]` => `_keys_to_ignore_on_load_missing  =  [r"h\.\d+\.attn\.causal_mask"]` to load correctly from CodeGen checkpoint without `causal_mask`.
2. Line 152, `causal_mask = self.causal_mask[:, :, key_length - query_length : key_length, :key_length]
` => `causal_mask = self.causal_mask[:, :, key_length - query_length : key_length, :key_length].bool()
` to alleviate potential user warning saying like `UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead.`.

* Revert the .bool()

Revert the .bool() and leave it to the future PR.

* Remove CLI spams with Whisper FeatureExtractor

Whisper feature extractor representation includes the MEL filters, a list of list that is represented as ~16,000 lines. This needlessly spams the command line. I added a `__repr__` method that replaces this list with a string "<array of shape (80, 201)>"

* Remove mel_filters from to_dict output  

Credits to @ArthurZucker

* remove unused import

* update feature extraction tests for the changes in to_dict

* adding note concerning use_node_local_storage

* overriding checkpoint.use_node_local_storage if save_on_each_node == True

* add more content

* add more content

* improve

* style

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Co-authored-by: Stas Bekman <stas@stason.org>

add with torch.no_grad() to Camembert integration test
Co-authored-by: Bibi <Bibi@katies-mac.local>

* v1 fix

* adapt from suggestions

* make style

* fix tests

* add gpu tests

* update docs

* fix other tests

* Apply suggestions from code review
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* better fix

* make fixup

* better example

* revert changes

* proposal

* more elegant solution

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

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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* added with torch.no_grad() to the integration tests and applied make style

* added with torch.no_grad() to xlm roberta forward pass

---------
Co-authored-by: Bibi <Bibi@katies-mac.local>

* Enforce single model initialization

* Add OneFormer example for problem 3

* Do it the Stas way

* Actually rename the uses...

* Rewrite test

* Try to change the test this way

* Fix all init slow/fast tests

* Break connection

* Fix more tests

* Fix test for initialization

* Remove custom test

* Quality

* Fix last failing tests

* The end?

* Fix inclusion of non py files in package

* No need for the **

* First draft

* More improvements

* More improvements

* Improve conversion script

* Convert all weights

* Make forward pass work

* Make logits match

* More improvements

* More improvements

* More improvements

* Use get_input_embeddings

* Improve some more

* Improve model tests

* Improve model tests

* More improvements

* Fix processor

* Update files

* Update prepare_inputs_for_generation

* More improvements

* Fix copies

* More fixes

* Make fixup

* More improvements

* Add support for seq2seq language model

* More improvements

* Fix test

* More improvements

* Improve conversion script

* Remove some todo's

* Fix README's

* Improve conversion script

* Fix generation

* Fix style and remove Blip2Model

* Fix model outputs

* More improvements

* Set eos_token_id in config

* Fix quality

* Small improvements

* Add processor tests

* More improvements

* Apply suggestions

* Apply suggestions

* Add integration test

* Update image URL

* Add integration test

* Fix model_type

* Update style

* Improve docs

* Add doc tests

* Fix copies

* Remove tests which are passing

* Improve some more

* Add tests for seq2seq language models

* Minor fix

* Convert more checkpoints

* finalize CI

* Fix blip and blip2 processors

* add `accelerate` support for `blip2`

* clean up

* make style

* Update conversion script

* Update conversion script some more

* Update organization

* revert toc file

* add blip-2 to toc file

* Some more improvements

* Fix docstring

* Improve docs

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

Update run_speech_recognition_ctc.py

There should be `# limitations under the License` line at the end of the documentation section.

begone slow tests

* Added clearml pipeline fix for when task is already initialized

* Correctly initialize

fix missing unfinished_sequences

Add `__len__` method to `_LazyAutoMapping`
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* add tests with multiple eos_token_ids

* make math.prod instead of sum

* make fixup

* fix long and also use np.prod since math.prod does not exist <python 3.8

* make fixup

* add prod util

* use prod util instead of np.prod

* make fixup

* previous .long location

* use tensor ops

* remove prod

* remove prod

* update device

* make fixup

* fix none

[tests] report_to none

docs: fix some references in PyTorch text classification readme

Bump cryptography from 36.0.2 to 39.0.1 in /examples/research_projects/decision_transformer (#21507)

Bump cryptography in /examples/research_projects/decision_transformer

Bumps [cryptography](https://github.com/pyca/cryptography) from 36.0.2 to 39.0.1.
- [Release notes](https://github.com/pyca/cryptography/releases)
- [Changelog](https://github.com/pyca/cryptography/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pyca/cryptography/compare/36.0.2...39.0.1

)

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

added with torch.no_grad() to the integration tests and applied make style
Co-authored-by: Bibi <Bibi@katies-mac.local>

check for mapping/dict in distributed_concat function

Co-authored-by: prajwal967 <user.email>

* doc: introduce new section for XLM-V model

* doc: mention more details for XLM-V integration

* docs: paper abstract in italics, model identifier for base model added

* doc: mention new XLM-V support

* auto: add XLM-V mapping

* doc: run make fix-copies ;)

* added inverse sqrt lr scheduler

* Updated get_scheduler in src/transformers/optimization.py

* Updated src/transformers/__init__.py

* Added inverse sqrt lr scheduler test

* Updated docs/source/en/main_classes/optimizer_schedules.mdx

* Ran style and quality scripts

* Fix get_inverse_sqrt_schedule docstring

* Comment implementation URL

* [tokenizer] sanitize saved config

* rm config["name_or_path"] test

* Remove mentions of flake8/isort

* Clean up inits

* Deall with all other inits

* Last special rule for dummy files

* Add limit_all_gathers option to fsdp_config and fix forward_prefetch bug

* Fix black issue

* Fix ruff failure

* Incorporate PR feedbacks

* Incorporate PR feedbacks

* Incorporate PR feedbacks

* Add a new test to check config attributes being used

* Add a new test to check config attributes being used

* Add a new test to check config attributes being used

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

* Apply suggestions

* Update allowed cases - part 1

* Update allowed cases - part 2

* final

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

* Add ("opt", ("GPT2Tokenizer", "GPT2TokenizerFast" if is_tokenizers_available() else None)),

* skip failing test

* Add ("opt", ("GPT2Tokenizer", "GPT2TokenizerFast" if is_tokenizers_available() else None)),

* skip failing test

Sanity check the type of id2label and label2id arguments of from_pretrained for TokenClassification models (#21490)

* Sanity check the type of id2label and label2id arguments of from_pretrained for TokenClassification models

* Incorporate PR feedbacks

* Incorporate PR feedbacks