GitLab

* add warning when using  with FSDP full shard

* fix style

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

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

* add hybrid shard warn

* fix style

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

Bump certifi in /examples/research_projects/visual_bert

Bumps [certifi](https://github.com/certifi/python-certifi) from 2023.7.22 to 2024.7.4.
- [Commits](https://github.com/certifi/python-certifi/compare/2023.07.22...2024.07.04

)

---
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  dependency-type: direct:production
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Revert "Fix `_init_weights` for `ResNetPreTrainedModel` (#31851)"

This reverts commit 4c8149d6.

Update modeling_utils.py

Add return type annotation to PreTrainedModel.from_pretrained

Bump zipp in /examples/research_projects/decision_transformer

Bumps [zipp](https://github.com/jaraco/zipp) from 3.7.0 to 3.19.1.
- [Release notes](https://github.com/jaraco/zipp/releases)
- [Changelog](https://github.com/jaraco/zipp/blob/main/NEWS.rst)
- [Commits](https://github.com/jaraco/zipp/compare/v3.7.0...v3.19.1

)

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- dependency-name: zipp
  dependency-type: direct:production
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Co-authored-by: Merve Noyan <mervenoyan@Merve-MacBook-Pro.local>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* init

* test

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

Co-authored-by: Joao Gante <joao@huggingface.co>

Signed-off-by: chenk <hen.keinan@gmail.com>

fix test

remove duplicate words

Add model

only test input_embeds, not decoder_input_embeds

* deprrecate `vocab_size` in other two VLMs

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

* depracate until 4.44

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

* enable strict signature

* this should not have been deleted

* recurrent_gemma too

* Fix wrong acclerator device setup when using MPS

* More robust TrainingArguments MPS handling

* Update training_args.py

* Cleanup

* fix

* fix

* fix

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

* symbolic trace supports inputs_embeds

* fix test?

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

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

* fix typo

* fix typo

* fix typos

* fix typo

* fix typos

Bump certifi in /examples/research_projects/lxmert

Bumps [certifi](https://github.com/certifi/python-certifi) from 2023.7.22 to 2024.7.4.
- [Commits](https://github.com/certifi/python-certifi/compare/2023.07.22...2024.07.04

)

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  dependency-type: direct:production
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Bump transformers in /examples/tensorflow/language-modeling-tpu

Bumps [transformers](https://github.com/huggingface/transformers) from 4.26.1 to 4.38.0.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](https://github.com/huggingface/transformers/compare/v4.26.1...v4.38.0

)

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* Rebase to main

* Fix attention implementation autoset for tex and vision configs

* Fixup

* Minor fixes

* Fix copies

* Fix attention_mask for FA2

* Add eqvivalence tests for siglip

* Remove right padding test

* Uncomment flaky

* Fix import

* Add to docs

* Fix test message

* Add sdpa

* Add sdpa equivalence test

* Add siglip sdpa to docs

* Fix typing for attention output

* Add sdpa tests

* Fix signature of FA2

* Autoset attn_implementation in config

* Rename bsz -> batch_size

* Move back autoset attn method

* Mark as flaky

* Correct attention mask padding

* [run-slow] siglip

* Add FA2 and sdpa docs

* Style fix

* Remove flaky for FA2 test

* Change attention implementation set

* Change attn_implementaiton propogation

* Fix typos

* Add modality to assert message

* Add more sdpa backends in test

* [run slow] siglip

* Add math sdpa backend for all options

* [run slow] siglip

Bump certifi from 2023.7.22 to 2024.7.4 in /examples/research_projects/decision_transformer (#31813)

Bump certifi in /examples/research_projects/decision_transformer

Bumps [certifi](https://github.com/certifi/python-certifi) from 2023.7.22 to 2024.7.4.
- [Commits](https://github.com/certifi/python-certifi/compare/2023.07.22...2024.07.04

)

---
updated-dependencies:
- dependency-name: certifi
  dependency-type: direct:production
...
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avoiding crash when BatchEncoding data is None

* First draft

* Add docs

* Clean up code

* Convert model

* Add image processor

* Convert Zoe_K

* More improvements

* Improve variable names and docstrings

* Improve variable names

* Improve variable names

* Replace nn.sequential

* More improvements

* Convert ZoeD_NK

* Fix most tests

* Verify pixel values

* Verify pixel values

* Add squeeze

* Update beit to support arbitrary window sizes

* Improve image processor

* Improve docstring

* Improve beit

* Improve model outputs

* Add figure

* Fix beit

* Update checkpoint

* Fix repo id

* Add _keys_to_ignore_on_load_unexpected

* More improvements

* Address comments

* Address comments

* Address comments

* Address comments

* Rename variable name

* Add backbone_hidden_size

* Vectorize

* Vectorize more

* Address comments

* Clarify docstring

* Remove backbone_hidden_size

* Fix image processor

* Remove print statements

* Remove print statement

* Add integration test

* Address comments

* Address comments

* Address comments

* Address comments

* Add requires_backends

* Clean up

* Simplify conversion script

* Simplify more

* Simplify more

* Simplify more

* Clean up

* Make sure beit is loaded correctly

* Address comment

* Address bin_configurations

* Use bin_configurations

* Convert models, add integration tests

* Fix doc test

* Address comments

* Unify regressor classes

* Clarify arguments

* Improve resize_image

* Add num_relative_features

* Address comment

* [run-slow]beit,data2vec,zoedepth

* [run-slow]beit,data2vec,zoedepth

* Address comments

* Address comment

* Address comment

* Replace nn.TransformerEncoderLayer and nn.TransformerEncoder

* Replace nn.MultiheadAttention

* Add attributes for patch transformer to config

* Add tests for ensure_multiple_of

* Update organization

* Add tests

* [run-slow] beit data2vec

* Update ruff

* [run-slow] beit data2vec

* Add comment

* Improve docstrings, add test

* Fix interpolate_pos_encoding

* Fix slow tests

* Add docstring

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

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

* Improve tests and docstrings

* Use run_common_tests

* Improve docstrings

* Improve docstrings

* Improve tests

* Improve tests

* Remove print statements

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

* Depth Anything: update conversion script for V2

* Update docs

* Style

* Revert "Update docs"

This reverts commit be0ca47ea1be4f3cd9aa2113bdd8efcc9959119e.

* Add docs for depth anything v2

* Add depth_anything_v2 to MODEL_NAMES_MAPPING

Done similarly to Flan-T5: https://github.com/huggingface/transformers/pull/19892/files

* Add tip in original docs

* handle new weight norm

* fix

* fix trailing space

* fix galore lr display with lr schedulers

* style

* add some tests to check for displayed lrs

* copy-paste err for warmup steps

* standardize the default lr to be only in the optimizer

* trying out my luck with the reads

* cast image features to model.dtype where needed to support FP16 or other precision in pipelines

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

* Use .to instead

* Add FP16 pipeline support for zeroshot audio classification

* Remove unused torch imports

* Add docs on FP16 pipeline

* Remove unused import

* Add FP16 tests to pipeline mixin

* Add fp16 placeholder for mask_generation pipeline test

* Add FP16 tests for all pipelines

* Fix formatting

* Remove torch_dtype arg from is_pipeline_test_to_skip*

* Fix format

* trigger ci

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

* Repeating an important warning in the chat template docs

* Update docs/source/en/chat_templating.md
Co-authored-by: Lysandre Debut <hi@lysand.re>

* Reword for clarity

* Reword for clarity

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Co-authored-by: Lysandre Debut <hi@lysand.re>

* Add siglip loss function

* Update docs

* Enable training tests
[experimental] enable GC training tests as it has worked for my own data

* Remove test_training* overrides to enable training tests
[run_slow] siglip

* Skip training tests for Siglip text model and ImageClassificationModel
[run_slow] siglip

* Skip GC training tests for SiglipForImageClassification

* Explicitly skip training tests for SiglipVisionModel
Add skip reason for training tests for SiglipTextModel

* Remove copied from to fix CI

* Code agent: allow function persistence between steps

* skip 3 7b tests

* fix

* fix

* fix

* [run-slow] gemma

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

* Update CometCallback to allow reusing of the running experiment

* Fixups

* Remove useless TODO

* Add checks for minimum version of the Comet SDK

* Fix documentation and links.

Also simplify how the Comet Experiment name is passed

* exclude compile time from metrics computation

* fix the quality issue

return correct device when ACCELERATE_TORCH_DEVICE is defined

* Fix serialization

* style

* add test

* fixed ClapProcessor to merge all values output from the feature extractor into the returned BatchEncoding.

* fixed trailing whitespace

* Add torch_empty_cache_steps to TrainingArguments

* Fix formatting

* Add torch_empty_cache_steps to docs on single gpu training

* Remove check for torch_empty_cache_steps <= max_steps

* Captalize Tip

* Be device agnostic

* Fix linting