GitLab

Added one more confirmed speaker, zoom links and gcal event links

* Add option to save on each training node

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Address review comments
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

this PR is fixing an incorrect attribute - probably some tests are needed?

* [WIP] Easily train a new fast tokenizer from a given one

* Fix test

* Roll out to other tokenizers and add tests

* Fix bug with unk id and add emoji to test

* Really use something different in test

* Implement special tokens map

* Map special tokens in the Transformers tokenizers

* Fix test

* Make test more robust

* Fix test for BPE

* More robust map and test

Co-authored-by SaulLu

* Test file

* Stronger tests
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>

* Map unk token for Wordpiece and address review comment

* Fix lowercase test and address review comment

* Fix all tests

* Simplify test

* Fix tests for realsies

* Easily train a new fast tokenizer from a given one - tackle the special tokens format (str or AddedToken) (#12420)

* Propose change in tests regarding lower case

* add new test for special tokens types

* put back the test part about decoding

* add feature: the AddedToken is re-build with the different mapped content

* Address review comment: simplify AddedToken building
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* Update src/transformers/tokenization_utils_fast.py
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

Co-authored-by: Jipeng Huang <jihuan@microsoft.com>

* fix_torch_device_generate_test

* remove @

* finish

* finish

* correct style

* add readme

* update readme and add requirements

* Update examples/flax/summarization/README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix TFWav2Vec2 SpecAugment

* Invert masks

* Feedback changes

* Add OOV error to ASR models

* Feedback changes

* Rename target to labels in DetrFeatureExtractor

* Update DetrFeatureExtractor tests accordingly

* Improve docs of DetrFeatureExtractor

* Improve docs

* Make style

* [models] respect dtype of the model when instantiating it

* cleanup

* cleanup

* rework to handle non-float dtype

* fix

* switch to fp32 tiny model

* improve

* use dtype.is_floating_point

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix the doc

* recode to use explicit torch_dtype_auto_detect, torch_dtype args

* docs and tweaks

* docs and tweaks

* docs and tweaks

* merge 2 args, add docs

* fix

* fix

* better doc

* better doc
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix_torch_device_generate_test

* remove @

* add length computatan

* finish masking

* finish

* upload

* fix some bugs

* finish

* fix dependency table

* correct tensorboard

* Apply suggestions from code review

* correct processing

* slight change init

* correct some more mistakes

* apply suggestions

* improve readme

* fix indent

* Apply suggestions from code review
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* correct tokenizer

* finish

* finish

* finish

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* Tensorflow MLM example

* Add CLM example

* Style fixes, adding missing checkpoint code from the CLM example

* Fix TPU training, avoid massive dataset warnings

* Fix incorrect training length calculation for multi-GPU training

* Fix incorrect training length calculation for multi-GPU training

* Refactors and nitpicks from the review

* Style pass

* Adding README

* fix_torch_device_generate_test

* remove @

* finish

* correct summary writer

* correct push to hub

* fix indent

* finish

* finish

* finish

* finish

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* debug albert einsum

* Fix matmul computation

* Let's use torch linear layer.

* Style.

* fix_torch_device_generate_test

* remove @

* boom boom

* correct typos

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

* Apply suggestions from code review
Co-authored-by: Suzana Ilić <io.suzanai@gmail.com>

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

* added cotext manager to datasets map

* fixed style and spaces

* fixed warning of deprecation

* changed desc

* add dependency table sync verification

* improve the message

* improve the message

* revert

* ready to merge

Before the code could not be used for validation only because of this line:
extension = data_args.train_file.split(".")[-1]
was assuming that extension must be extracted from the training dataset. This line would run regardless of the training or validation options of the user. This would lead to an error if the user only wants to run an evaluation only and does not want to do train (because the training file does not exist). I modified it to extract extension from the training file if the user wants to do train and extract it from the validation file if the user wants to run eval. This way the code can be used for both training and validation separately.

[Documentation] Warn that DataCollatorForWholeWordMask is limited to BertTokenizer-like tokenizers (#12371)

* Notify users that DataCollatorForWholeWordMask is limited to BertTokenier-like tokenizers

* Fix code formatting

* added log_level

* fix comment

* fixed log_level

* Trigger CI

* Unfied logging

* simplified args for log_level

* main_process_first context manager

* handle multi-node, add context description

* sync desc

* fixed multiplechoice tokenization

The model would have seen two sequences:
1. [CLS]prompt[SEP]prompt[SEP]
2. [CLS]choice0[SEP]choice1[SEP]
that is not correct as we want a contextualized embedding of prompt and choice

* removed outer brackets for proper sequence generation

* Replace NotebookProgressReporter by ProgressReporter in Ray Tune run

* Move to local import

* port bigbird script

* adapt script a bit

* change location

* adapt more

* save progress

* init commit

* style

* dataset script tested

* readme add

* fix distributed_concat for scalar outputs

* Update README.md

* fixed typo (#12356)

* simplify fix with terser syntax
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Trigger CI
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: michal pitr <21157924+MichalPitr@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>