* add RMSProp to Trainer

* revert some change

* Update src/transformers/trainer.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>

Move misplaced line, improve code comment

* default to use it

* style

* Fixed nll with label_smoothing to nll

* Resolved conflict by rebase

* Fixed nll with label_smoothing to nll

* Resolved conflict by rebase

* Added label_smoothing to config file

* Fixed nits

* report grad_norm during training

* support getting grad_norm from deepspeed

* Update base.py

* Fix a typo

* generated text on A10G

* generated text in CI

* Apply suggestions from code review

add explanatory comments

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

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

output_logits option behaves like output_scores, but returns the raw, unprocessed prediction logit scores,
ie. the values before they undergo logit processing and/or warping. The latter happens by default for the
regular output scores.

It's useful to have the unprocessed logit scores in certain circumstances. For example, unprocessed logit scores
are very useful with causallm models when one wants to determine the probability of a certain answer, e.g.
when asking a question with a yes/no answer. In that case getting the next-token probabilities of both "yes" and
"no" (and/or their relative ratio) is of interest for classification. The reason for getting these _before_ logit
processing and/or warping is b/c a) that can change the probabilities or b) reject the tokens of interest / reduce
the number of tokens to just 1.

For an example use-case see paper TabLLM: Few-shot Classification of Tabular Data with Large Language Models
by Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, and David Sontag.
https://arxiv.org/abs/2210.10723



In addition:
- added dedicated unit test: tests/generation/test_utils/test_return_unprocessed_logit_scores
  which tests return of logics with output_logits=True in generation.
- set output_logits=True in all other generation unit tests, that also have output_scores=True.

Implemented @gante's and @amyeroberts review feedback

Co-authored-by: kx79wq <max.baak@ing.com>

* Add resource

* Add more resources

* Add resources

* Apply suggestions from code review

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

* Remove mention

* Remove pipeline tags

---------

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

* change version

* nuke

* this doesn't make sense

* update some requirements.py

* revert + no main

* nits

* change cache number

* more pin

* revert

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

Fix test

The link in evaluation was missing a hyphen between post and processing. I fixed this, for English only. Someone with the ability to do a global search/replace should fix the other languages (if indeed they have this issue)/

Update test_mixed_int8.py

* add peft support for AWQ

* Update src/transformers/quantizers/quantizer_awq.py

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

* fix

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

* Add task_summary to es/_toctree.yml

* Add task_summary.md to docs/es

* Change title of task_summary.md

* Translate firsts paragraphs

* Translate middle paragraphs

* Translte the rest of the doc

* Edit firts paragraph

* Add chat support to text generation pipeline

* Better handling of single elements

* Deprecate ConversationalPipeline

* stash commit

* Add missing add_special_tokens kwarg

* Update chat templating docs to refer to TextGenerationPipeline instead of ConversationalPipeline

* Add TF

 tests

* @require_tf

* Add type hint

* Add specific deprecation version

* Remove unnecessary do_sample

* Remove todo - the discrepancy has been resolved

* Update src/transformers/tokenization_utils_base.py

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

* Update src/transformers/pipelines/text_generation.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 trainer test

* Update tests/trainer/test_trainer.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>

* Added option to set tracking URI for MLflowCallback.

* Added option to set tracking URI for MLflowCallback.

* Changed  to  in docstring.

* pass through trust_remote_code for dynamically loading unregistered tokenizers specified by config
add test

* change directories back to previous directory after test

* fix ruff check

* Add a note to that block for future in case we want to remove it later

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

Update trainer.py

* fix heuristic num_assistant_tokens_schedule

* Update src/transformers/generation/configuration_utils.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/generation/candidate_generator.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update utils.py

check that candidate_generator.assistant_model exists since some some speculations (like ngram and PLD) don't have assistant_model attribute

* Update src/transformers/generation/candidate_generator.py

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

* Update tests/generation/test_utils.py

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

* make fixup

* merge conflict

* fix docstring

* make fixup

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Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* made changes for object detection models

* added support for segmentation models.

* Made changes for segmentaion models

* Changed import statements

* solving conflicts

* removed conflicts

* Resolving commits

* Removed conflicts

* Fix : Pixel_mask_value set to False

* fix max_length for inputs_embeds

* make style

* Update src/transformers/generation/utils.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Static Cache: load models with MQA or GQA (#28975)

* fix

* fix tests

* fix tests

* Update src/transformers/generation/utils.py

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

* more fixes

* make style

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

* Script & Manual edition

* Update

Update utils.py

removed redundant field

* Patch to skip currently failing tests

* Whoops - wrong place

Update modeling_utils.py

* Update ms_deform_attn_cuda.cu

* Update ms_deform_attn_cuda.cuh

* Update modeling_deformable_detr.py

* Update src/transformers/models/deformable_detr/modeling_deformable_detr.py

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

* Update modeling_deformable_detr.py

* python utils/check_copies.py --fix_and_overwrite

* Fix dtype missmatch error

* Update test_modeling_deformable_detr.py

* Update test_modeling_deformable_detr.py

* Update modeling_deformable_detr.py

* Update modeling_deformable_detr.py

---------

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

* enable graident checkpointing in DetaObjectDetection

* fix missing part in original DETA

* make style

* make fix-copies

* Revert "make fix-copies"

This reverts commit 4041c86c29248f1673e8173b677c20b5a4511358.

* remove fix-copies of DetaDecoder

* enable swin gradient checkpointing

* fix gradient checkpointing in donut_swin

* add tests for deta/swin/donut

* Revert "fix gradient checkpointing in donut_swin"

This reverts commit 1cf345e34d3cc0e09eb800d9895805b1dd9b474d.

* change supports_gradient_checkpointing pipeline to PreTrainedModel

* Revert "add tests for deta/swin/donut"

This reverts commit 6056ffbb1eddc3cb3a99e4ebb231ae3edf295f5b.

* Revert "Revert "fix gradient checkpointing in donut_swin""

This reverts commit 24e25d0a14891241de58a0d86f817d0b5d2a341f.

* Simple revert

* enable deformable detr gradient checkpointing

* add gradient in encoder

* add cuda_custom_kernel function in MSDA

* make style and fix input of DetaMSDA

* make fix-copies

* remove n_levels in input of DetaMSDA

* minor changes

* refactor custom_cuda_kernel like yoso format
https://github.com/huggingface/transformers/blob/0507e69d34f8902422eb4977ec066dd6bef179a0/src/transformers/models/yoso/modeling_yoso.py#L53

* wow I was scared!

* fix everything

* nits

* make it BC?

* add todo

* nits

* is_tracing should still be used to pass tracing tests

* nits

* some nits to make sure genration works with static cache uncompiled

* fix sdpa

* fix FA2 for both static and dynamic in a better way?

* style

* fix-copies

* fix fix copies

* fix sequential beam searcg

* style

* use `keys_to_ignore`

* nit

* correct dtype inference when init

* :( the fix for FA2 is still not optimal to investigate!

* styling

* nits

* nit

* this might work better

* add comment

* Update src/transformers/models/llama/modeling_llama.py

* "position_ids" -> "cache_position"

* style

* nit

* Remove changes that should no be propagatted just yet

* Apply suggestions from code review

* Styling

* make sure we raise an errir for static cache with FA2 enabled

* move  to the bottom of the signature

* style

* Update src/transformers/models/llama/modeling_llama.py

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

* Update src/transformers/models/llama/modeling_llama.py

* nit in the name

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