GitLab

remove dataset with restrictive license

* Pass datasets trust_remote_code

* Pass trust_remote_code in more tests

* Add trust_remote_dataset_code arg to some tests

* Revert "Temporarily pin datasets upper version to fix CI"

This reverts commit b7672826.

* Pass trust_remote_code in librispeech_asr_dummy docstrings

* Revert "Pin datasets<2.20.0 for examples"

This reverts commit 833fc17a.

* Pass trust_remote_code to all examples

* Revert "Add trust_remote_dataset_code arg to some tests" to research_projects

* Pass trust_remote_code to tests

* Pass trust_remote_code to docstrings

* Fix flax examples tests requirements

* Pass trust_remote_dataset_code arg to tests

* Replace trust_remote_dataset_code with trust_remote_code in one example

* Fix duplicate trust_remote_code

* Replace args.trust_remote_dataset_code with args.trust_remote_code

* Replace trust_remote_dataset_code with trust_remote_code in parser

* Replace trust_remote_dataset_code with trust_remote_code in dataclasses

* Replace trust_remote_dataset_code with trust_remote_code arg

* Support multiple validation datasets when dataloader_persistent_workers=True

* Test support of multiple validation datasets

Bumps [idna](https://github.com/kjd/idna) from 2.8 to 3.7.
- [Release notes](https://github.com/kjd/idna/releases)
- [Changelog](https://github.com/kjd/idna/blob/master/HISTORY.rst)
- [Commits](https://github.com/kjd/idna/compare/v2.8...v3.7

)

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

* fix

* use accelerator device count

* ci fix

Bumps [idna](https://github.com/kjd/idna) from 2.8 to 3.7.
- [Release notes](https://github.com/kjd/idna/releases)
- [Changelog](https://github.com/kjd/idna/blob/master/HISTORY.rst)
- [Commits](https://github.com/kjd/idna/compare/v2.8...v3.7

)

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

Bump idna in /examples/research_projects/decision_transformer

Bumps [idna](https://github.com/kjd/idna) from 3.3 to 3.7.
- [Release notes](https://github.com/kjd/idna/releases)
- [Changelog](https://github.com/kjd/idna/blob/master/HISTORY.rst)
- [Commits](https://github.com/kjd/idna/compare/v3.3...v3.7

)

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

Fix Logits Processors device misplacement

fix

* xpu: support xpu backend from stock pytorch (>=2.4)

Fixes: https://github.com/huggingface/transformers/issues/31237

XPU backend is available in the stock PyTorch starting from
version 2.4, see [1]. This commit extends huggingface transformers
to support XPU from both IPEX and the stock pytorch. IPEX is being
tried first.

See: https://github.com/pytorch/pytorch/issues/114842
Requires: https://github.com/huggingface/accelerate/pull/2825

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>

* xpu: enable gpt2 and decision_transformer tests for xpu pytorch backend

Note that running xpu tests requires TRANSFORMERS_TEST_DEVICE_SPEC=spec.py
passed to the test runner:

  import torch
  DEVICE_NAME = 'xpu'
  MANUAL_SEED_FN = torch.xpu.manual_seed
  EMPTY_CACHE_FN = torch.xpu.empty_cache
  DEVICE_COUNT_FN = torch.xpu.device_count
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>

---------
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>

Remove empty tests

change embeddings padding warning to warning_once

* Fix SpeechT5

* add test foward with labels and attention mask

* make style

* fix sdpa musicgen

* make style

* remove copied from statement from Musicgen SDPA

Temporarily pin datasets upper version

* Update french translation of tutoriel_pipeline.md

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update docs/source/fr/tutoriel_pipeline.md
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

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

* add initial design for uniform processors + align model

* fix mutable default 👀

* add configuration test

* handle structured kwargs w defaults + add test

* protect torch-specific test

* fix style

* fix

* fix assertEqual

* move kwargs merging to processing common

* rework kwargs for type hinting

* just get Unpack from extensions

* run-slow[align]

* handle kwargs passed as nested dict

* add from_pretrained test for nested kwargs handling

* [run-slow]align

* update documentation + imports

* update audio inputs

* protect audio types, silly

* try removing imports

* make things simpler

* simplerer

* move out kwargs test to common mixin

* [run-slow]align

* skip tests for old processors

* [run-slow]align, clip

* !$#@!! protect imports, darn it

* [run-slow]align, clip

* [run-slow]align, clip

* update doc

* improve documentation for default values

* add model_max_length testing

This parameter depends on tokenizers received.

* Raise if kwargs are specified in two places

* fix

* expand VideoInput

* fix

* fix style

* remove defaults values

* add comment to indicate documentation on adding kwargs

* protect imports

* [run-slow]align

* fix

* remove set() that breaks ordering

* test more

* removed unused func

* [run-slow]align

* Let's try moving chat templates out of IDEFICS and into the generic ProcessorMixin

* Chat templates should not be mandatory

* Chat templates should not be mandatory

* Not all classes will have default chat templates

* stash commit

* Add chat template docstring

* Clean up docstring

* Add chat templates to LLaVA/LLaVA-next

* Docstring fixup

* Quick IDEFICS2 fixup

* Remove some old references to the Conversation class

* make fixup

[QoL fix] [Image processing] Add warning on assumption of channel dim and avoid infering when inputs are PIL.Image (#31364)

* Add warning on assumption of channel dim
Use PIL info whenever possible to decide channel axis

* Fix ruff format

* Remove type checking
Improve warning message

* Update src/transformers/models/siglip/image_processing_siglip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/image_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/image_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Change JSON serialization to custom json.dumps to prevent escaping of "<", ">", "&", "'"

* caller has control over the order, remove sort_key=True

* Move tojson into a proper function and expose a couple of other args

---------
Co-authored-by: jun.4 <jun.4@kakaobrain.com>
Co-authored-by: Matt <rocketknight1@gmail.com>

Bump jupyter-core in /examples/research_projects/visual_bert

Bumps [jupyter-core](https://github.com/jupyter/jupyter_core) from 4.6.3 to 4.11.2.
- [Release notes](https://github.com/jupyter/jupyter_core/releases)
- [Changelog](https://github.com/jupyter/jupyter_core/blob/main/CHANGELOG.md)
- [Commits](https://github.com/jupyter/jupyter_core/compare/4.6.3...4.11.2

)

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

* shard saving from hf hub

* index = None

* fix tests

* indent

Badge underline fix

Fix relative import

* docs: fix broken link

* fix link

Renamed loss to losses to suppress UnboundLocalError
Co-authored-by: Your Name <you@example.com>

* fix idefics cache

* fix tests

* Support import declaration in Code Agent

* Draft fast image processors

* Draft working fast version

* py3.8 compatible cache

* Enable loading fast image processors through auto

* Tidy up; rescale behaviour based on input type

* Enable tests for fast image processors

* Smarter rescaling

* Don't default to Fast

* Safer imports

* Add necessary Pillow requirement

* Woops

* Add AutoImageProcessor test

* Fix up

* Fix test for imagegpt

* Fix test

* Review comments

* Add warning for TF and JAX input types

* Rearrange

* Return transforms

* NumpyToTensor transformation

* Rebase - include changes from upstream in ImageProcessingMixin

* Safe typing

* Fix up

* convert mean/std to tesnor to rescale

* Don't store transforms in state

* Fix up

* Update src/transformers/image_processing_utils_fast.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Warn if fast image processor available

* Update src/transformers/models/vit/image_processing_vit_fast.py

* Transpose incoming numpy images to be in CHW format

* Update mapping names based on packages, auto set fast to None

* Fix up

* Fix

* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test

* Update src/transformers/models/vit/image_processing_vit_fast.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Add equivalence and speed tests

* Fix up

---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>