GitLab

* remove use_auth_token from from_config

* restore use_auth_token from_pretrained run_t5_mlm_flax

* Fix RESOURCE_EXHAUSTED error for large datasets on Flax example scripts

* using np.permutation for creating batch_idx

* train_samples_idx -> training_samples_idx

* fix type hints

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

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.

* Correct Logging of Eval metric to Tensorboard

An empty dictionary ``eval_metrics`` was being logged, is replaced by ``eval_metric`` which is the output dictionary of ``metric.compute()``.

* Remove unused variable

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

* Fix t5 shard on TPU Pods

The current script doesn't work properly on a TPU pod because the global batch is not divided correctly per host.
This pull request fixes this issue by dividing the global batch to each host before it is shared on each host.

* fix style
Co-authored-by: ahmed-elnaggar <ahmed.elnaggar@allianz.com>

* fix formatting and remove use_auth

* Add use_auth_token to Flax examples

* [examples] max samples can't be bigger than then len of dataset

* do tf and flax

Fix typo in comment: proprocessed -> preprocessed

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Updates the default branch from master to main

* Links from `master` to `main`

* Typo

* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Speedup training by using numpy instead of jnp for batch shuffling
Co-authored-by: Yeb Havinga <y.t.havinga@mgrid.net>

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

* Harder check for IndexErrors in QA scripts

* Make test stronger

fix typo

* add a section about GPUs

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* 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

* add image captioning example

* update README

* fix style & quality

* simplify

* apply review suggestions

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Apply review suggestions

* add comments about using np instead jax array

* remove unused lines

* add model creation script

* only support from_pretrained

* fix style

* fix

* not use cache_dir when creating model

* fix tokenizer creation

* update README

* fix quality

* apply suggestion

* simplify some blocks

* Update examples/flax/image-captioning/README.md


* Update examples/flax/image-captioning/run_image_captioning_flax.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* apply suggestion
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

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

* use jax and jnp instead of numpy in data_loader

* return batches as np.ndarray

* use custom training arguments

* update tests

* make tensorboard optional

* update test_fetcher for flax examples

* make the tests slow