GitLab

check max_position_embeddings

fix: handle logging of scalars in wandb summary

fixes:  #29430

* add tests for batching support

* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* fixes and comments

* use cosine distance for conv models

* skip mra model testing

* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* finzalize  and make style

* check model type by input names

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

* fixed batch size for all testers

* Revert "fixed batch size for all testers"

This reverts commit 525f3a0a058f069fbda00352cf202b728d40df99.

* add batch_size for all testers

* dict from model output

* do not skip layoutlm

* bring back some code from git revert

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

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

* clean-up

* where did minus go in tolerance

* make whisper happy

* deal with consequences of losing minus

* deal with consequences of losing minus

* maskformer needs its own test for happiness

* fix more models

* tag flaky CV models from Amy's approval

* make codestyle

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

Update quantization.md

* update

* update

* update

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

* Set env var to hold Keras at Keras 2

* Add Amy's update

* make fixup

* Use a warning instead

* Update legacy Repository usage in `examples/pytorch/text-classification/run_glue_no_trainer.py`

Marked for deprecation here https://huggingface.co/docs/huggingface_hub/guides/upload#legacy-upload-files-with-git-lfs

* Fix import order

* Replace all example usage of deprecated Repository

* Fix remaining repo call and rename args variable

* Revert removing creation of gitignore files and don't change research examples

Implemented add_pooling_layer argument

* Fix type (determine)

* ruff

* Update src/transformers/models/mamba/configuration_mamba.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 examples to stop passing None to compile(), rework example invocation for run_text_classification.py

* Add Amy's fix

fix fuyu docs

* Experimental loading of MLX files

* Update exception message

* Add test

* Style

* Use model from hf-internal-testing

* Update add_new_model.md

* Update docs/source/en/add_new_model.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

Fixed broken link for Resources -> Token Classification -> Finetuning BERT for named-entity

* Add missing localized READMEs to the copies check

* Run check to resolve all inconsistencies

fix error: TypeError: Object of type Tensor is not JSON serializable trainer
Co-authored-by: Zach Mueller <muellerzr@gmail.com>

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

[Docs] Fix FastSpeech2Conformer links

* add USE_TORCH_XLA env

* rename torch_tpu to torch_xla

* better is_torch_xla_available; fix some fsdp and performance issues

* fix format

* fix bug when pjrt_device is cpu

* fix bug

* fix the deprecation handling

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Co-authored-by: anw90 <ang868@gmail.com>
Co-authored-by: wangang.wa <wangang.wa@alibaba-inc.com>

* Fixing error #29332. The _check_and_enable_flash_attn_2() method receives a check_device_map parameter and fails.

* style fixup

* add: initial script to train clm fim

* fix: if training model from scratch, new tokens will be added and embeddings resized

* fix: fixed attention_mask errors when generating FIM data

* fix: file formatted using black

* add: run_fim_no_trainer.py and fixed some comments in run_fim.py

* add: added fim examples to the README.md and ran code fixup

* fix: little bug in both fim training scripts

* fix: remove comment from notebook and added a note on fim related params

* fix: minor typo in README

* add: suggested minor changes to README and run_fim.py

* add: gradient_accumulation_steps and gradient_checkpointing args

* add: improved model embedding resizing

* add: pad_to_multiple_of and attn_implementation params

* add: requested minor changes

* add: deepspeed zero compatibility

* add: resize embeddings layer with zero3 support for fim model initialization

* post merge update

* nit

* oups

feat: use `warning_advice` instead of tensorflow warning

* Fix eval thread fork bomb

* Keep eval dl persistent and prepare after so free_memory doesn't destroy it

* Add note

* Quality

[tests] use the correct `n_gpu` in `TrainerIntegrationTest::test_train_and_eval_dataloaders` for XPU (#29307)

* fix n_gpu

* fix style

fix total silence input with no_speech_threshold

fix FSDP config

* Make sliding window size inclusive in eager attention

* Fix tests

* fix stablelm dropout argument type error

* fix docs of _flash_attention_forward

* fix all docs of _flash_attention_forward

* fix docs of _flash_attention_forward in starcoder2

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Co-authored-by: oliang <oliang@tencent.com>

* use torch_device

* skip for XPU

* Update tests/generation/test_utils.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 image-to-text batch incorrect output issue
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* add ci test
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* update ci test
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* add sacremoses check

* fix style

* for FlaubertTokenizer

* HerbertTokenizer fix

* add typeHint

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

* make less skipped

* make quality

* remove import

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

* left-padding test revisited

* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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

Potential typo in mlx support

* 🐛 Fix vision encoder decoder positional arg

* ✅

 Add test for VisionEncoderDecoder with LayoutLMv3 encoder

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Co-authored-by: Nick DeGroot <1966472+nickthegroot@users.noreply.github.com>

* Set `inputs` as kwarg in `TextClassificationPipeline`

This change has been done to align the `TextClassificationPipeline` with the rest of the pipelines, and to be able to e.g. `pipeline(**{"inputs": "text"})` which wouldn't be possible since the `*args` were being used instead.

* Add `noqa: C409` on `tuple([inputs],)`

Even though is discouraged by the linter, the cast `tuple(list(...),)` is required here, as otherwise the original list in `inputs` will be transformed into a `tuple` and the elements 1...N will be ignored by the `Pipeline`

* Run `ruff format`

* Simplify `tuple` conversion with `(inputs,)`
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

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Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Fall back to pytorch model for now

* Fix up