* initial commit
* First draft that gets outputs without crashing!
* Add all the ported openfold dependencies
* testing
* Restructure config files for ESMFold
* Debugging to find output discrepancies
* Mainly style
* Make model runnable without extra deps
* Remove utils and merge them to the modeling file
* Use correct gelu and remove some debug prints
* More cleanup
* Update esm docs
* Update conversion script to support ESMFold properly
* Port some top-level changes from ESMFold repo
* Expand EsmFold docstrings
* Make attention_mask optional (default to all 1s)
* Add inference test for ESMFold
* Use config and not n kwargs
* Add modeling output class
* Remove einops
* Remove chunking in ESM FFN
* Update tests for ESMFold
* Quality
* REpo consistency
* Remove tree dependency from ESMFold
* make fixup
* Add an error in case my structure map function breaks later
* Remove needless code
* Stop auto-casting the LM to float16 so CPU tests pass
* Stop auto-casting the LM to float16 so CPU tests pass
* Final test updates
* Split test file
* Copyright and quality
* Unpin PyTorch to see built doc
* Fix config file to_dict() method
* Add some docstrings to the output
* Skip TF checkpoint tests for ESM until we reupload those
* make fixup
* More docstrings
* Unpin to get even with main
* Flag example to write
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* Add Example docstring to DebertaConfig
* Add configuration_deberta to documentation_tests
* Add microsoft/deberta-base to example docstring
* Fix example docstring mistake
* Support segformer fx
* Add fx_compatible attribute to test_modeling_segformer.py
* Update glpn model (fx support)
glpn model was copied from segformer.
* Update utils/fx.py | add semantic-segmentation
for SegformerForSemanticSegmentation model
* Fix minor import order(isort)
* Add random input generation for segformer fx
Co-authored-by: noelbird <lduldu00228@gmail.com>
* Let inputs of fast tokenizers be tuples as well as lists
* Update src/transformers/tokenization_utils_fast.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Style
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Wip
* Add safetensors support for TensorFlow
* First tests
* Add final test for now
* Retrigger CI like this
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Change the import of kenlm from github to pypi
* Change the import of kenlm from github to pypi in circleci config
* Fix code quality issues
* Fix isort issue, add kenlm in extras for audio
* Add kenlm to deps
* Add kenlm to deps
* Commit 'make fixup' changes
* Remove version from kenlm deps
* commit make fixup changes
* Remove manual installation of kenlm
* Remove manual installation of kenlm
* Remove manual installation of kenlm
* Add missing information on token_type_ids for roberta model
* Fix code format issues
* Fix code format issues
* Add more explicit document for token_type_ids for roberta
* Fix flake8 issues
* Fix flake8 issues
* Fix flake8 issues
* Fix flake8 issues
* Fix flake8 issues
* Factored out some code in the image-segmentation pipeline
Re-enable `small_model_pt`.
Re-enable `small_model_pt`.
Enabling the current test with the current values.
Debugging the values on the CI.
More logs ? Printing doesn't work ?
Using the CI values instead. Seems to be a Pillow sensitivity.
Added a test showcasing that models not supporting some tasks get a
clear error.
Factored out code.
Further factor out.
Fixup.
Bad rebase.
Put `panoptic` before `instance` as it should be a superset.
* Fixing tests.
* Adding subtasks tests
+ Fixes `instance` segmentation which was broken due to default and
non kwargs arguments.
* Fix bad replace.
