GitLab

* Port core files + ESM (because ESM code is odd)

* Search-replace in modelling code

* Fix up transfo_xl as well

* Fix other core files + tests (still need to add correct import to tests)

* Fix cookiecutter

* make fixup, fix imports in some more core files

* Auto-add imports to tests

* Cleanup, add imports to sagemaker tests

* Use correct exception for importing tf_keras

* Fixes in modeling_tf_utils

* make fixup

* Correct version parsing code

* Ensure the pipeline tests correctly revert to float32 after each test

* Ensure the pipeline tests correctly revert to float32 after each test

* More tf.keras -> keras

* Add dtype cast

* Better imports of tf_keras

* Add a cast for tf.assign, just in case

* Fix callback imports

* Proposed fix for TF example now running on safetensors.

* Adding more warnings and returning keys.

* Trigger CI

* Trigger CI

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Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

* TF image classification script

* Update requirements

* Fix up

* Add tests

* Update test fetcher
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix directory path

* Adding `zero-shot-object-detection` pipeline doctest. (#20274)

* Adding `zero-shot-object-detection` pipeline doctest.

* Remove nested_simplify.

* Add generate kwargs to `AutomaticSpeechRecognitionPipeline` (#20952)

* Add generate kwargs to AutomaticSpeechRecognitionPipeline

* Add test for generation kwargs

* Trigger CI

* Data collator returns np

* Update feature extractor -> image processor

* Bug fixes - updates to reflect changes in API

* Update flags to match PT & run faster

* Update instructions - Maria's comment

* Update examples/tensorflow/image-classification/README.md

* Remove slow decorator

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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: bofeng huang <bofenghuang7@gmail.com>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

* Finished QA example

* Dodge a merge conflict

* Update text classification and LM examples

* Update NER example

* New Keras metrics WIP, fix NER example

* Update NER example

* Update MC, summarization and translation examples

* Add XLA warnings when shapes are variable

* Make sure batch_size is consistently scaled by num_replicas

* Add PushToHubCallback to all models

* Add docs links for KerasMetricCallback

* Add docs links for prepare_tf_dataset and jit_compile

* Correct inferred model names

* Don't assume the dataset has 'lang'

* Don't assume the dataset has 'lang'

* Write metrics in text classification

* Add 'framework' to TrainingArguments and TFTrainingArguments

* Export metrics in all examples and add tests

* Fix training args for Flax

* Update command line args for translation test

* make fixup

* Fix accidentally running other tests in fp16

* Remove do_train/do_eval from run_clm.py

* Remove do_train/do_eval from run_mlm.py

* Add tensorflow tests to circleci

* Fix circleci

* Update examples/tensorflow/language-modeling/run_mlm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update examples/tensorflow/test_tensorflow_examples.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update examples/tensorflow/translation/run_translation.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update examples/tensorflow/token-classification/run_ner.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Fix save path for tests

* Fix some model card kwargs

* Explain the magical -1000

* Actually enable tests this time

* Skip text classification PR until we fix shape inference

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

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

* 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