GitLab

* 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

* Initial setup

* Metrics

* Overfit on two batches

* Train 40 epochs

* Memory leak debugging

* Trainer fine-tuning

* Draft

* Fixup

* Trained end-to-end

* Add requirements

* Rewrite evaluator

* nits

* Add readme

* Add instance-segmentation to the table

* Support void masks

* Remove sh

* Update docs

* Add pytorch test

* Add accelerate test

* Update examples/pytorch/instance-segmentation/README.md

* Update examples/pytorch/instance-segmentation/run_instance_segmentation.py

* Update examples/pytorch/instance-segmentation/run_instance_segmentation_no_trainer.py

* Update examples/pytorch/instance-segmentation/run_instance_segmentation_no_trainer.py

* Update examples/pytorch/instance-segmentation/run_instance_segmentation.py

* Fix consistency oneformer

* Fix imports

* Fix imports sort

* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update examples/pytorch/instance-segmentation/run_instance_segmentation.py
Co-authored-by: Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com>

* Add resources to docs

* Update examples/pytorch/instance-segmentation/README.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update examples/pytorch/instance-segmentation/README.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove explicit model_type argument

* Fix tests

* Update readme

* Note about other models

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Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Training script for object detection

* Evaluation script for object detection

* Training script for object detection with eval loop outside trainer

* Trainer DETR finetuning

* No trainer DETR finetuning

* Eval script

* Refine object detection example with trainer

* Remove commented code and enable telemetry

* No trainer example

* Add requirements for object detection examples

* Add test for trainer example

* Readme draft

* Fix uploading to HUB

* Readme improvements

* Update eval script

* Adding tests for object-detection examples

* Add object-detection example

* Add object-detection resources to docs

* Update README with custom dataset instructions

* Update year

* Replace valid with validation

* Update instructions for custom dataset

* Remove eval script

* Remove use_auth_token

* Add copied from and telemetry

* Fixup

* Update readme

* Fix id2label

* Fix links in docs

* Update examples/pytorch/object-detection/run_object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update examples/pytorch/object-detection/run_object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Move description to the top

* Fix Trainer example

* Update no trainer example

* Update albumentations version

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Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Script & Manual edition

* Update

* Remove `task` arg in `load_dataset` in image-classification example

* Manage case where "train" is not in dataset

* Add new args to manage image and label column names

* Similar to audio-classification example

* Fix README

* Update tests

* fix

* [test-all] commit

* fix

* [test-all] commit

* [test-all] commit

* fix

* fix

* fix

* fix

* fix

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

Change thresh

Unused param

* Fix example tests from failing

* CHange thresh

* Fix translation

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

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* Fix all tests

* Adjust test arguments and use a new example test

Fix metric calculation in examples and setup tests to run on multi-gpu for no_trainer scripts (#17331)

* Fix length in no_trainer examples

* Add setup and teardown

* Use new accelerator config generator to automatically make tests able to run based on environment

1. Fixes evaluation errors popping up when you train/eval on squad v2 (one was newly encountered and one that was previously reported Running SQuAD 1.0 sample command raises IndexError #15401 but not completely fixed).
2. Removes boolean arguments that don't use store_true. Please, don't use these: *ANY non-empty string is being converted to True in this case and this clearly is not the desired behavior (and it creates a LOT of confusion).
3. All no-trainer test scripts are now saving metric values in the same way (with the right prefix eval_), which is consistent with the trainer-based versions.
4. Adds forgotten model.eval() in the no-trainer versions. This improved some results, but not everything (see the discussion in the end). Please, see the F1 scores and the discussion below.

* Add first draft

* Improve README and run fixup

* Make script aligned with other scripts, improve README

* Improve script and add test

* Remove print statement

* Apply suggestions from code review

* Add num_labels to make test pass

* Improve README

* Add first draft from previous PR

* First draft

* Improve README and remove num_labels

* Make script more aligned with other scripts

* Improve README and apply suggestion from code review

* Change tracking to store_true

* Remove step param and use it in the log dictionary directly

* use vars(args) when passing args to init_trackers

* Include tracking tests since tensorboard is already a dep

Move declaration of log streams to before tests, so that results won't get compounded on top of each other

* Fixed some bugs involving saving during epochs
* Added tests mimicking the existing examples tests
* Added in json exporting to all `no_trainer` examples for consistency 

* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* refactor run_flax_glue.py

* updated readme

* rm unused import and args typo fix

* refactor

* make consistent arg name across task

* has_tensorboard check

* argparse -> argument dataclasses

* refactor according to review

* fix

* use custom training arguments

* update tests

* make tensorboard optional

* update test_fetcher for flax examples

* make the tests slow

* add test for glue

* add tests for clm

* fix clm test

* add summrization tests

* more tests

* fix few tests

* add test for t5 mlm

* fix t5 mlm test

* fix tests for multi device

* cleanup

* ci job

* fix metric file name

* make t5 more robust