* Start PR doc
* Cleanup the quality checks and document them
* Add reference in the contributing guide
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Rename file as per review suggestion
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Fix of issue #13327: Wrong weight initialization for TF t5 model
* run black formatter
* fix typo
* remove my name tag from comments
Co-authored-by: Shirron <dan.shirron@intel.com>
* Adding support for `truncation` parameter on `feature-extraction`
pipeline.
Fixes#14183
* Fixing tests on ibert, longformer, and roberta.
* Rebase fix.
* minimal fixes to run DataCollatorForWholeWordMask with return_tensors="np" and return_tensors="tf"
* more consinstent implementation for numpy_mask_tokens
* Add cross attentions to TFGPT2Model
* change to is_pt_tf_cross_test
* A minor correction to a comment
* Remove n_ctx when creating self.crossattention
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add Beit model ouput class
* inherting from BaseModelOuputWithPooling
* updated docs if use_mean_pooling is False
* added beit specific outputs in model docs
* changed the import path
* Fix docs
Co-authored-by: Niels Rogge <niels.rogge1@gmail.com>
* check test_configuration_tie
* Fix test_configuration_tie
* make test slow again
* Remove property and use model.module.bind
* revert to slow test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Add first draft
* Make forward pass work
* Improve conversion script
* Add notebook that checks if it works
* Add BeitForSemanticSegmentation to the tests
* More improvements
* Make BeitForSemanticSegmentation consistent with Segformer
* Small bug fix
* Add BeitForSemanticSegmentation to docs
* Make sure model doesn't output hidden states when the user doesn't want to
* Make it possible to convert the large model
* Fix issue
* Fix conversion script for large model
* Add auxiliary_head option to semantic segmentation model
* Apply suggestions from @sgugger's review
* Apply suggestions from code review
* Fix failing test
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Fixing image segmentation for inference mode.
* Update src/transformers/pipelines/base.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Adding `handle_long_generation` paramters for `text-generation` pipeline.
* More error handling
* Fixing tests by dropping tf support on this functionality, it needs
`max_new_tokens` to make it possible to understand user's intent.
Otherwise, `max_length` == `tokenizer.model_max_length` <
input_ids.shape[0].
* Fixing doc ?
* Doc ?
* Remove link from doc.
* Catched an issue on roberta.
* Damn doc.
* Non BC proposal ?
* Cleaning the fix ?
* Finally using only a test override.
* Don't need to modify this.
* Bad print.
* Add the support for the fast (rust) implementation of BlenbderbotTokenizer
* Fix a converter and a typo in a doc
* Apply the patil-suraj's suggestion
* (Nitpick) Fast tokenization -> Fast Tokenization in doc
* Apply the SaulLu's suggestion
* Apply Narsil's suggestion to fix test pipelines
* Add encoder_no_repeat_ngram_size according to the Narsil's suggestion
* Revert the last (unnecessary) commit
* Override pipeline config for Blenderbot to allow for larger pos. emb.
* make fix-copies
* Remove n_ctx from configs
* Fix GPTJ and OpenAIGPT, both are acceptable breaking changes as there are no configs such that it breaks
* Remove unecessary n_positions from TFOpenAIGPT
* First draft
* Make tuple output more readable
* Replace assertions by value errors
* Make it possible to predict_with_generate for vision and speech models
* Adapt Seq2SeqTrainer to work with VisionEncoderDecoder/SpeechEncoderDecoder
* Add deprecation warning
* Add copied from statements to vision and speech encoder decoders
* Fix failing test
* Apply @patrickvonplaten's suggestion
* Use reshape instead of view for consistency
* First draft
* Make style & quality
* Improve conversion script
* Add print statement to see actual slice
* Make absolute tolerance smaller
* Fix image classification models
* Add post_process_semantic method
* Disable padding
* Improve conversion script
* Rename to ForSemanticSegmentation, add integration test, remove post_process methods
* Improve docs
* Fix code quality
* Fix feature extractor tests
* Fix tests for image classification model
* Delete file
* Add is_torch_available to feature extractor
* Improve documentation of feature extractor methods
* Apply suggestions from @sgugger's code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply some more suggestions of code review
* Rebase with master
* Fix rebase issues
* Make sure model only outputs hidden states when the user wants to
* Apply suggestions from code review
* Add pad method
* Support padding of 2d images
* Add print statement
* Add print statement
* Move padding method to SegformerFeatureExtractor
* Fix issue
* Add casting of segmentation maps
* Add test for padding
* Add small note about padding
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
