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

* Remove deprecated logic and warnings

* Add back some code that seems to be important...

* Let's just add all he nllb stuff back; removing it is a bit more involved

* Remove kwargs

* Remove more kwargs

* Update legacy Repository usage in `examples/pytorch/text-classification/run_glue_no_trainer.py`

Marked for deprecation here https://huggingface.co/docs/huggingface_hub/guides/upload#legacy-upload-files-with-git-lfs

* Fix import order

* Replace all example usage of deprecated Repository

* Fix remaining repo call and rename args variable

* Revert removing creation of gitignore files and don't change research examples

Co-authored-by: p_spozzhang <p_spozzhang@tencent.com>

While using `run_clm.py`,[^1] I noticed that some files were being added
to my global cache, not the local cache. I set the `cache_dir` parameter
for the one call to `evaluate.load()`, which partially solved the
problem. I figured that while I was fixing the one script upstream, I
might as well fix the problem in all other example scripts that I could.

There are still some files being added to my global cache, but this
appears to be a bug in `evaluate` itself. This commit at least moves
some of the files into the local cache, which is better than before.

To create this PR, I made the following regex-based transformation:
`evaluate\.load\((.*?)\)` -> `evaluate\.load\($1,
cache_dir=model_args.cache_dir\)`. After using that, I manually fixed
all modified files with `ruff` serving as useful guidance. During the
process, I removed one existing usage of the `cache_dir` parameter in a
script that did not have a corresponding `--cache-dir` argument
declared.

[^1]: I specifically used `pytorch/language-modeling/run_clm.py` from
v4.34.1 of the library. For the original code, see the following URL:
https://github.com/huggingface/transformers/tree/acc394c4f5e1283c19783581790b3dc3105a3697/examples/pytorch/language-modeling/run_clm.py.

fixed the broken links belogs to dataset library of transformers

* Remove the torch main_process_first context manager from TF examples

* Correctly set num_beams=1 in our examples, and add a guard in GenerationConfig.validate()

* Update src/transformers/generation/configuration_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

Add missing spaces in adjacent strings

`jnp.array` is a function, not a type:
https://jax.readthedocs.io/en/latest/_autosummary/jax.numpy.array.html


so it never makes sense to use `jnp.array` in a type annotation. Presumably the intent was to write `jnp.ndarray` aka `jax.Array`.
Co-authored-by: Peter Hawkins <phawkins@google.com>

* docs: add space to docs

* docs: remove reduntant space

* pytorch examples

* pytorch mim no trainer

* cookiecutter

* flax examples

* missed line in pytorch run_glue

* tensorflow examples

* tensorflow run_clip

* tensorflow run_mlm

* tensorflow run_ner

* tensorflow run_clm

* pytorch example from_configs

* pytorch no trainer examples

* Revert "tensorflow run_clip"

This reverts commit 261f86ac1f1c9e05dd3fd0291e1a1f8e573781d5.

* fix: duplicated argument

* fix

* fix

* fix

* fix

* fix

* fix

* fix

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

* pytorch examples

* tensorflow examples

* flax examples

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

* Fix .push_to_hub and cleanup get_full_repo_name usage

* Do not rely on Python bool conversion magic

* request changes

allow only test_file in pytorch and flax summarization

* 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

* Adapt repository creation to latest hf_hub

* Update all examples

* Fix other tests, add Flax examples

* Address review comments

* Compute true loss

* fixup

* final

* final

* final

* Update examples/flax/language-modeling/run_bart_dlm_flax.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* jax.tree_map => jax.tree_util.tree_map

* Compute true loss

* final

* fixup

* final

* final

* Update examples/flax/language-modeling/run_bart_dlm_flax.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* jax.tree_map => jax.tree_util.tree_map
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* [JAX] Replace all jax.tree_* calls with jax.tree_util.tree_*

* fix double tree_util

* [Flax] Add remat (gradient checkpointing)

* fix variable naming in test

* flip: checkpoint using a method

* fix naming

* fix class naming

* apply PVP's suggestions from code review

* add gradient_checkpointing to examples

* Add gradient_checkpointing to run_mlm_flax

* Add remat to longt5

* Add gradient checkpointing test longt5

* Fix args errors

* Fix remaining tests

* Make fixup & quality fixes

* replace kwargs

* remove unecessary kwargs

* Make fixup changes

* revert long_t5_flax changes

* Remove return_dict and copy to LongT5

* Remove test_gradient_checkpointing
Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>

* zero chance anyone's using that constant no?

* `transformers-cli login` => `huggingface-cli login`

* `transformers-cli repo create` => `huggingface-cli repo create`

* `make style`

* Fix ROUGE add example check and update README

* Stay consistent in values

* Preliminary work on tokenizers

* Quality + fix tests

* Treat processors

* Fix pad

* Remove all uses of  in tests, docs and examples

* Replace all as_target_tokenizer

* Fix tests

* Fix quality

* Update examples/flax/image-captioning/run_image_captioning_flax.py
Co-authored-by: amyeroberts <amy@huggingface.co>

* Style
Co-authored-by: amyeroberts <amy@huggingface.co>

Currently, tensorflow examples use the `load_metric` function from
Datasets library, commit migrates function call to `load` function
from Evaluate library.

* [Flax] Fix incomplete batches in example scripts

* fix dataloader batching

* convert jnp batch idxs to np array

* add missing `pad_shard_unpad` to final prediction generate step

* only `pad_shard_unpad` at inference time

* merge conflicts

* remove incomplete batch step from eval

* fix run_qa.py

* add `pad_shard_unpad` to run_flax_ner.py

* add `pad_shard_unpad` to run_flax_glue.py

* add `pad_shard_unpad` to run_image_classification.py

* make style

* fix mlm flax eval batches

* remove redundant imports

* generalize decay_mask_fn to find all layernorm params

* fixup

* generalising decay_mask_fn

* remove use_auth_token from from_config

* restore use_auth_token from_pretrained run_t5_mlm_flax

* 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

* 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

* 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

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

* use custom training arguments

* update tests

* 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

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

* use Repository for push_to_hub

* update readme

* update other flax scripts

* update readme

* update qa example

* fix push_to_hub call

* fix typo

* fix more typos

* update readme

* use abosolute path to get repo name

* fix glue script