GitLab

* [FlaxBert] Add ForCausalLM

* make style

* fix output attentions

* Add RobertaForCausalLM

* remove comment

* fix fx-to-pt model loading

* remove comment

* add modeling tests

* add enc-dec model tests

* add big_bird

* add electra

* make style

* make repo-consitency

* add to docs

* remove roberta test

* quality

* amend cookiecutter

* fix attention_mask bug in flax bert model tester

* tighten pt-fx thresholds to 1e-5

* add 'copied from' statements

* amend 'copied from' statements

* amend 'copied from' statements

* quality

* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length

* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length

* correct t5 tokenizer

* correct t5 tokenizer

* fix test

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

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

* Clean up setup.py

* Trigger CI

* Upgrade Python used

* Make sacremoses optional

* Pickle

* First draft

* Add YolosForObjectDetection

* Make forward pass work

* Add mid position embeddings

* Add interpolation of position encodings

* Add expected values

* Add YOLOS to tests

* Add integration test

* Support tiny model as well

* Support all models in conversion script

* Remove mid_pe_size attribute

* Make more tests pass

* Add model to README and fix config

* Add copied from statements

* Rename base_model_prefix to vit

* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP

* Apply suggestions from code review

* Apply more suggestions from code review

* Convert remaining checkpoints

* Improve docstrings

* Add YolosFeatureExtractor

* Add feature extractor to docs

* Add corresponding tests

* Fix style

* Fix docs

* Apply suggestion from code review

* Fix bad rebase

* Fix some more bad rebase

* Fix missing character

* Improve docs and variable names
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* Update all examples to properly calculate progress bar

* Propagate and fix imports

* Clean up tests

* Make fixup
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* add torch.no_grad when in eval mode

* make style quality

* [FlaxSpeechEncoderDecoder] Fix bug in `decoder_module`

* [FlaxEncoderDecoder] Fix bug in `decoder_module`

* Add meta proxy

* Uses meta data to trace data dependent control-flow

* Remove commented class

* Handles torch creating functions

* Added type annotation to fix tracing

* Tracing works for everything but T5 and GPT-J

* Almost all previously supported models pass

* All architectures can be traced except T5

* Intermediate commit to have a trace of the comparison operators for HFProxy

* Everything works, except loss computation

* Everything works

* Removed unused import

* Overriden methods do not use underlying ops (linear and torch.matmul), and model attributes are copied to the traced version

* Fix torch_matmul_override

* Change attributes reference to deepcopy

* Remove breakpoint and add torch_index_override

* Small fix

* Fix typo

* Replace asserts by explicit exceptions

* Add translating guide

* Add the check

* add missing ckpts

* add a list to ignore

* call the added check script

* better regex pattern
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Result of new doc style with fixes

* Add last two files

* Bump hf-doc-builder

* Replace dict/BatchEncoding instance checks by Mapping

* Typo

This reverts commit 4f3a14e3.

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

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

* dd parameter --config_overrides for run_mlm_wwm.py

* linter

* fix

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

The emoji version must be either 0.5.4 or 0.6.0. Newer emoji versions have been updated to newer versions of the Emoji Charts, thus not consistent with the one used for pre-processing the pre-training Tweet corpus (i.e. not consistent with the vocab).

* Add -e flag

* add check

* create new keys

* run python setup.py build install

* add comments

* change to develop
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

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

* Fix doc notebooks links

* Remove missing section

* Fixup all examples