GitLab

* Pin optax version

* Pin flax too

* Fixup

* Use accelerate for device management

* Add accelerate to setup
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding Llama FastTokenizer support.

- Requires https://github.com/huggingface/tokenizers/pull/1183 version
- Only support byte_fallback for llama, raise otherwise (safety net).
- Lots of questions are special tokens

How to test:

```python

from transformers.convert_slow_tokenizer import convert_slow_tokenizer
from transformers import AutoTokenizer
from tokenizers import Tokenizer

tokenizer = AutoTokenizer.from_pretrained("huggingface/llama-7b")

if False:
    new_tokenizer = Tokenizer.from_file("tok.json")
else:
    new_tokenizer = convert_slow_tokenizer(tokenizer)
    new_tokenizer.save("tok.json")

strings = [
    "This is a test",
    "生活的真谛是",
    "生活的真谛是[MASK]。",
    # XXX: This one is problematic because of special tokens
    # "<s> Something something",
]

for string in strings:
    encoded = tokenizer(string)["input_ids"]
    encoded2 = new_tokenizer.encode(string).ids

    assert encoded == encoded2, f"{encoded} != {encoded2}"

    decoded = tokenizer.decode(encoded)
    decoded2 = new_tokenizer.decode(encoded2)

    assert decoded.strip() == decoded2, f"{repr(decoded)} != {repr(decoded2)}"
```

The converter + some test script.

The test script.

Tmp save.

Adding Fast tokenizer + tests.

Adding the tokenization tests.

Correct combination.

Small fix.

Fixing tests.

Fixing with latest update.

Rebased.

fix copies + normalized added tokens  + copies.

Adding doc.

TMP.

Doc + split files.

Doc.

Versions + try import.

Fix Camembert + warnings -> Error.

Fix by ArthurZucker.

Not a decorator.

* Fixing comments.

* Adding more to docstring.

* Doc rewriting.

* [setup] migrate setup script to `pyproject.toml`

* [setup] cleanup configurations

* remove unused imports

* [setup] drop deprecated `distutils` usage

* drop deprecated `distutils.util.strtobool` usage

* fix import order

* reformat docstring by `doc-builder`

* Pin tensorflow-text to go with tensorflow

* Make it more convenient to pin TensorFlow

* setup don't like f-strings

* [deepspeed] offload + non-cpuadam optimizer exception doc

* deps

* time to say goodbye, torch 1.7 and 1.8

* clean up torch_int_div

* clean up is_torch_less_than_1_8-9

* update

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

* Add kernel size to NATTEN's QK arguments.

The new NATTEN 0.14.5 supports PyTorch 2.0, but also adds an additional
argument to the QK operation to allow optional RPBs.

This ends up failing NATTEN tests.

This commit adds NATTEN back to circleci and adds the arguments to get
it working again.

* Force NATTEN >= 0.14.5

* Use PyAV instead of Decord

* Get frame indices

* Fix number of frames

* Update src/transformers/models/videomae/image_processing_videomae.py

* Fix up

* Fix copies

* Update timesformer doctests

* Update docstrings

* Update setup.py

* suggestions

* Fix inclusion of non py files in package

* No need for the **

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* First draft

* Add initial draft of conversion script

* Convert all weights

* Fix config

* Add image processor

* Fix DetaImageProcessor

* Run make fix copies

* Remove timm dependency

* Fix dummy objects

* Improve loss function

* Remove conv_encoder attribute

* Update conversion scripts

* Improve postprocessing + docs

* Fix copied from statements

* Add tests

* Improve postprocessing

* Improve postprocessing

* Update READMEs

* More improvements

* Fix rebase

* Add is_torchvision_available

* Add torchvision dependency

* Fix typo and README

* Fix bug

* Add copied from

* Fix style

* Apply suggestions

* Fix thanks to @ydshieh

* Fix another dependency check

* Simplify image processor

* Add scipy

* Improve code

* Add threshold argument

* Fix bug

* Set default threshold

* Improve integration test

* Add another integration test

* Update setup.py

* Address review

* Improve deformable attention function

* Improve copied from

* Use relative imports

* Address review

* Replace assertions

* Address review

* Update dummies

* Remove dummies

* Address comments, update READMEs

* Remove custom kernel code

* Add image processor tests

* Add requires_backends

* Add minor comment

* Update scripts

* Update organization name

* Fix defaults, add doc tests

* Add id2label for object 365

* Fix tests

* Update task guide

* Adapt repository creation to latest hf_hub

* Update all examples

* Fix other tests, add Flax examples

* Address review comments

* update pyknp to rhoknp

* fix linter

* fix linter

* fix linter

* fix linter

* fix linter

* support rhoknp==1.1.0, fix testcase

* Install sentencepiece in DS CI image

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

* 🚧 wip video classification pipeline

* 🚧 wip - add is_decord_available check

* 🐛 add missing import

* ✅ add tests

* 🔧 add decord to setup extras

* 🚧 add is_decord_available

* ✨ add video-classification pipeline

* 📝 add video classification pipe to docs

* 🐛 add missing VideoClassificationPipeline import

* 📌 add decord install in test runner

* ✅ fix url inputs to video-classification pipeline

* ✨ updates from review

* 📝 add video cls pipeline to docs

* 📝 add docstring

* 🔥 remove unused import

* 🔥 remove some code

* 📝 docfix

* add minimal working gpt2 tokenizer

* graph mode and output equivalence tests working

* not today tensorflow. serialization test passing!

* fix style, documentation, docstrings and all that jazz

* passing consistency checks

* move keras nlp to tf dependencies

* fix tf modeling utils and gpt2 attention to enable compiling

* fix (I hope) keras nlp dependencies

* rever changes on generation

* remove debug prints

* remove redundant tf dummy objects

* add from config, get config and max length settings to address review

* let flake ignore the error on distillation you are welcome

* test from config

* add padding test

* address sgugger review

* Add DiNAT

* Adds DiNAT + tests

* Minor fixes

* Added HF model

* Add natten to dependencies.

* Cleanup

* Minor fixup

* Reformat

* Optional NATTEN import.

* Reformat & add doc to _toctree

* Reformat (finally)

* Dummy objects for DiNAT

* Add NAT + minor changes

Adds NAT as its own independent model + docs, tests
Adds NATTEN to ext deps to ensure ci picks it up.

* Remove natten from `all` and `dev-torch` deps, add manual pip install to ci tests

* Minor fixes.

* Fix READMEs.

* Requested changes to docs + minor fixes.

* Requested changes.

* Add NAT/DiNAT tests to layoutlm_job

* Correction to Dinat doc.

* Requested changes.

* Try PT1.13 by removing torch scatter

* Skip failing tests

* Style

* Remvoe testing extras for repo utils

* Try with all decorators

* Try to wipe the cache

* Fix all tests?

* Try this way

* Fix comma

* Update to main

* Try with less deps

* Quality