* custom_models: tiny doc addition
* mention security feature earlier in the section
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* [Proposal] Adding ZeroShotImageClassificationPipeline
- Based on CLIP
* WIP, Resurection in progress.
* Resurrection... achieved.
* Reword handling different `padding_value` for `feature_extractor` and
`tokenizer`.
* Thanks doc-builder !
* Adding docs + global namespace `ZeroShotImageClassificationPipeline`.
* Fixing templates.
* Make the test pass and be robust to floating error.
* Adressing suraj's comments on docs mostly.
* Tf support start.
* TF support.
* Update src/transformers/pipelines/zero_shot_image_classification.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* doc for adding a model to the hub
* run make style
* resolved conversation
* removed a line
* removed )
* Update docs/source/add_new_model.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update docs/source/add_new_model.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* make style
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Added all files, PoolFormerFeatureExtractor still failing tests
* Fixed PoolFormerFeatureExtractor not being able to import
* Completed Poolformer doc
* Applied Suggested fixes
* Fixed errors in modeling_auto.py
* Fix feature extractor, convert docs to Markdown, styling of code
* Remove PoolFormer from check_repo and fix integration test
* Remove Poolformer from check_repo
* Fixed configuration_poolformer.py docs and removed inference.py from poolformer
* Ran with black v22
* Added PoolFormer to _toctree.yml
* Updated poolformer doc
* Applied suggested fixes and added on README.md
* Did make fixup and make fix-copies, tests should pass now
* Changed PoolFormer weights conversion script name and fixed README
* Applied fixes in test_modeling_poolformer.py and modeling_poolformer.py
* Added PoolFormerFeatureExtractor to AutoFeatureExtractor API
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
* TF generate start refactor
* Add tf tests for sample generate
* re-organize
* boom boom
* Apply suggestions from code review
* re-add
* add all code
* make random greedy pass
* make encoder-decoder random work
* further improvements
* delete bogus file
* make gpt2 and t5 tests work
* finish logits tests
* correct logits processors
* correct past / encoder_outputs drama
* refactor some methods
* another fix
* refactor shape_list
* fix more shape list
* import shape
_list
* finish docs
* fix imports
* make style
* correct tf utils
* Fix TFRag as well
* Apply Lysandre's and Sylvais suggestions
* Update tests/test_generation_tf_logits_process.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Update src/transformers/tf_utils.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* remove cpu according to gante
* correct logit processor
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Add TensorFlow support for ONNX export
* Change documentation to mention conversion with Tensorflow
* Refactor export into export_pytorch and export_tensorflow
* Check model's type instead of framework installation to choose between TF and Pytorch
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Alberto Bégué <alberto.begue@della.ai>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>
* added classes to get started with constrained beam search
* in progress, think i can directly force tokens now but not yet with the round robin
* think now i have total control, now need to code the bank selection
* technically works as desired, need to optimize and fix design choices leading to undersirable outputs
* complete PR #1 without disjunctive decoding
* removed incorrect tests
* Delete k.txt
* Delete test.py
* Delete test.sh
* revert changes to test scripts
* genutils
* full implementation with testing, no disjunctive yet
* shifted docs
* passing all tests realistically ran locally
* removing accidentally included print statements
* fixed source of error in initial PR test
* fixing the get_device() vs device trap
* fixed documentation docstrings about constrained_beam_search
* fixed tests having failing for Speech2TextModel's floating point inputs
* fix cuda long tensor
* added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search
* deleted accidentally added test halting code with assert False
* code reformat
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
* fixing based on comments on PR
* took out the testing code that should but work fails without the beam search moditification ; style changes
* fixing comments issues
* docstrings for ConstraintListState
* typo in PhrsalConstraint docstring
* docstrings improvements
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* PoC for a ProcessorMixin class
* Documentation
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Roll out to other processors
* Add base feature extractor class in init
* Use args and kwargs
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add wrapper classes
* convert inner layers to tf
* Add TF Encoder and Decoder layers
* TFSpeech2Text models
* Loadable model
* TF model with same outputs as PT model
* test skeleton
* correct tests and run the fixup
* correct attention expansion
* TFSpeech2Text pask_key_values with TF format
* electra is added to onnx supported model
* add google/electra-base-generator for test onnx module
Co-authored-by: Lewis Tunstall <lewis.c.tunstall@gmail.com>
