GitLab

* add jit mode option and model wrap

* Update src/transformers/training_args.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/training_args.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* refine code

* Update src/transformers/trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/trainer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add ut and refine code

* code refine

* refine code

* add inference doc

* Update src/transformers/trainer.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Update src/transformers/trainer.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* add cpu inference performance doc

* Update perf_infer_cpu.mdx

* Update perf_infer_cpu.mdx

* Update performance.mdx

* Update _toctree.yml

* refine jit func naming

* Update _toctree.yml

* Delete perf_infer_gpu_one.mdx

* Update perf_infer_cpu.mdx

* Update docs/source/en/perf_infer_cpu.mdx
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* add none check before jit

* Update docs/source/en/perf_infer_cpu.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/en/perf_infer_cpu.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Fix doc builder Dockerfile
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Initial commit

* Make some fixes

* Make PT model full forward pass

* Drop TF & Flax implementation, fix copies etc

* Add Flax model and update some corresponding stuff

* Drop some TF things

* Update config and flax local attn

* Add encoder_attention_type to config

* .

* Update docs

* Do some cleansing

* Fix some issues -> make style; add some docs

* Fix position_bias + mask addition + Update tests

* Fix repo consistency

* Fix model consistency by removing flax operation over attn_mask

* [WIP] Add PT TGlobal LongT5

* .

* [WIP] Add flax tglobal model

* [WIP] Update flax model to use the right attention type in the encoder

* Fix flax tglobal model forward pass

* Make the use of global_relative_attention_bias

* Add test suites for TGlobal model

* Fix minor bugs, clean code

* Fix pt-flax equivalence though not convinced with correctness

* Fix LocalAttn implementation to match the original impl. + update READMEs

* Few updates

* Update: [Flax] improve large model init and loading #16148

* Add ckpt conversion script accoring to #16853 + handle torch device placement

* Minor updates to conversion script.

* Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM

* gpu support + dtype fix

* Apply some suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* * Remove (de)parallelize stuff
* Edit shape comments
* Update README.md
* make fix-copies

* Remove caching logic for local & tglobal attention

* Apply another batch of suggestions from code review

* Add missing checkpoints
* Format converting scripts
* Drop (de)parallelize links from longT5 mdx

* Fix converting script + revert config file change

* Revert "Remove caching logic for local & tglobal attention"

This reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46.

* Stash caching logic in Flax model

* Make side relative bias used always

* Drop caching logic in PT model

* Return side bias as it was

* Drop all remaining model parallel logic

* Remove clamp statements

* Move test files to the proper place

* Update docs with new version of hf-doc-builder

* Fix test imports

* Make some minor improvements

* Add missing checkpoints to docs
* Make TGlobal model compatible with torch.onnx.export
* Replace some np.ndarray with jnp.ndarray

* Fix TGlobal for ONNX conversion + update docs

* fix _make_global_fixed_block_ids and masked neg  value

* update flax model

* style and quality

* fix imports

* remove load_tf_weights_in_longt5 from init and fix copies

* add slow test for TGlobal model

* typo fix

* Drop obsolete is_parallelizable and one warning

* Update __init__ files to fix repo-consistency

* fix pipeline test

* Fix some device placements

* [wip]: Update tests -- need to generate summaries to update expected_summary

* Fix quality

* Update LongT5 model card

* Update (slow) summarization tests

* make style

* rename checkpoitns

* finish

* fix flax tests
Co-authored-by: phungvanduy <pvduy23@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patil-suraj <surajp815@gmail.com>

* Add FP16 supporot for sagemaker model parallel

* minor fix

* fix indentation

* handle mix precision exception for smmp

* minor fix

* remove amp implementation on SMMP

* remove redundant stuff

* reformat trainer

* restyling

* reformat

* enable cpu distribution training using mpirun

*command like
*    mpirun -n 2 python3 run_qa.py --no_cuda --xpu_backend ccl xxxx
*MASTER_ADDR and MASTER_PORT should be set as env
*export MASTER_ADDR=127.0.0.1
*export MASTER_PORT=29500
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* fix according to the review comment
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* use accelerate logic for cpu distribution training to set "RANK","LOCAL_RANK","WORLD_SIZE" environment
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* allow scope from trainer arg

* add ray_scope to training args

* escape double quotes

* make style && quality

* attempt to solve doc style issues

* splitting up URLs for style

* make fixup

* Update src/transformers/training_args.py
Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>

* make style
Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>

I'm guessing that the intention was to have the `_no_split_modules` class attribute for `GPTNeoXPreTrainedModel` to be set to `["GPTNeoXLayer"]`, akin to how its set as `["GPTJBlock"]` for `GPTJPreTrainedModel`.

If this is incorrect, please feel free to just close the PR.

Thanks!

* Fix dtype getters

* Proper fix for dtype getter

* Style and commant

* Always use last for consistency

* Quality

Co-authored-by: Saint <saint@st-mini.local>

* wip

* rebase

* all tests pass

* rebase

* ready for PR

* address comments

* fix styles

* add require_torch to pipeline test

* remove remote image to improve CI consistency

* address comments; fix tf/flax tests

* address comments; fix tf/flax tests

* fix tests; add alias

* repo consistency tests

* Update src/transformers/pipelines/visual_question_answering.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* address comments

* Update src/transformers/pipelines/visual_question_answering.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* merge

* Update src/transformers/models/auto/modeling_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* merge
Co-authored-by: Sijun He <sijunhe@Sijuns-MacBook-Pro.local>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* [BigBirdFlaxTests] Make tests slow

* up

* correct black with new version

- use CodeParrot scores of v1.1
- change evaluation command to use accelerate

* Raise RepoNotFoundError in case of 401

* Include changes from revert-17646-skip_repo_not_found

* Add a comment

* 💄 Code quality

* 💚 Update `get_from_cache` test

* 💚 Code quality & skip failing test

VisibleDeprecationWarning is addressed by specifying dtype=object when creating numpy array.
Update code based on review feedback.
Undo whitespace changes to tokenization_utils_base.py.
Co-authored-by: I like data <ilikedata@nym.hush.com>

Bumps [cookiecutter](https://github.com/cookiecutter/cookiecutter) from 1.7.2 to 2.1.1.
- [Release notes](https://github.com/cookiecutter/cookiecutter/releases)
- [Changelog](https://github.com/cookiecutter/cookiecutter/blob/master/HISTORY.md)
- [Commits](https://github.com/cookiecutter/cookiecutter/compare/1.7.2...2.1.1

)

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

* enable crop_center method to handle (W, H, C) images

* minor style and comment edits

* move clip image utils to image_utils.py

* dont default to square images

* fix typo, revert change to test file

* edit convert_rgb comments

* Add Italian translation for autoclass_tutorial.mdx

* Fix synthesis
Co-authored-by: martina.fumanelli <martina.fumanelli@MBP-di-martinafumanelli.local>

* convert assertion to raised exception in debertav2

* change assert to raise exception in deberta

* fix messages

* pre-build deepspeed
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* [modeling_utils] torch_dtype/auto fixes

* add test

* apply suggestions

* add missing fallback

* Renaming things

* Use for else
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

When we're preparing the tensors for CPU for postprocessing, we need
to upgrade the `float16` to `float32` since CPUs don't have instructions
for `[b]float16`.

* Fix very long job failure text in Slack report
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Adding `top_k` and `sort` arguments to `text-classification` pipeline.

- Deprecate `return_all_scores` as `top_k` is more uniform with other
  pipelines, and a superset of what `return_all_scores` can do.
  BC is maintained though.
  `return_all_scores=True` -> `top_k=None`
  `return_all_scores=False` -> `top_k=1`

- Using `top_k` will imply sorting the results, but using no argument
  will keep the results unsorted for backward compatibility.

* Remove `sort`.

* Fixing the test.

* Remove bad doc.

* Use shape_list to safely get shapes

* Add relevant test

* Tidy and add metrics

* Resolve dynamic shaping issues and move test

* Tidy up and all samples in batch

* Formatting