* 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>
* add xlm roberta xl
* add convert xlm xl fairseq checkpoint to pytorch
* fix init and documents for xlm-roberta-xl
* fix indention
* add test for XLM-R xl,xxl
* fix model hub name
* fix some stuff
* up
* correct init
* fix more
* fix as suggestions
* add torch_device
* fix default values of doc strings
* fix leftovers
* merge to master
* up
* correct hub names
* fix docs
* fix model
* up
* finalize
* last fix
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add copied from
* make style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* clean commit of changes
* apply review feedback, make edits
* fix backticks, minor formatting
* 🖍 make fixup and minor edits
* 🖍 fix # in header
* 📝 update code sample without from_pt
* 📝 final review
* Added missing code in exemplary notebook - custom datasets fine-tuning
Added missing code in tokenize_and_align_labels function in the exemplary notebook on custom datasets - token classification.
The missing code concerns adding labels for all but first token in a single word.
The added code was taken directly from huggingface official example - this [colab notebook](https://github.com/huggingface/notebooks/blob/master/transformers_doc/custom_datasets.ipynb).
* Changes requested in the review - keep the code as simple as possible
* First commit
* Add conversion script
* Make conversion script work for base model
* More improvements
* Update conversion script, works for vqa
* Add indexing argument to meshgrid
* Make conversion script work for ViltForPreTraining
* Add ViltForPreTraining to docs
* Fix device issue
* Add processor
* Add MinMaxResize to feature extractor
* Implement call method of ViltProcessor
* Fix tests
* Add integration test
* Add loss calculation for VQA
* Improve tests
* Improve some more tests
* Debug tests
* Small improvements
* Add support for attention_mask
* Remove mask_it
* Add pixel_mask
* Add tests for ViltFeatureExtractor
* Improve tests
* Add ViltForNaturalLanguageVisualReasoning
* Add ViltForNaturalLanguageVisualReasoning to conversion script
* Minor fixes
* Add support for image_embeds, update docstrings to markdown
* Update docs to markdown
* Improve conversion script
* Rename ViltForPreTraining to ViltForMaskedLM
* Improve conversion script
* Convert docstrings to markdown
* Fix code example of retrieval model
* Properly convert masked language model
* Add integration test for nlvr
* Fix code quality
* Apply suggestions from code review
* Add copied from statements
* Fix pretrained_config_archive_map
* Fix docs
* Add model to README
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply more suggestions from code review
* Make code more readable
* Add ViltForNaturalLanguageVisualReasoning to the tests
* Rename ViltForVisualQuestionAnswering to ViltForQuestionAnswering
* Replace pixel_values_2 by single tensor
* Add hidden_states and attentions
* Fix one more test
* Fix all tests
* Update year
* Fix rebase issues
* Fix another rebase issue
* Remove ViltForPreTraining from auto mapping
* Rename ViltForImageRetrievalTextRetrieval to ViltForImageAndTextRetrieval
* Make it possible to use BertTokenizerFast in the processor
* Use BertTokenizerFast by default
* Rename ViltForNaturalLanguageVisualReasoning, define custom model output
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* First draft
* More improvements
* More improvements
* More improvements
* Fix embeddings
* Add conversion script
* Finish conversion script
* More improvements
* Fix forward pass
* Remove print statements
* Add weights initialization
* Add initialization of decoder weights
* Add support for other models in the conversion script
* Fix patch_size for huge model
* Fix most of the tests
* Fix integration test
* Fix docs
* Fix archive_list
* Apply suggestions from code review
* Improve documentation
* Apply more suggestions
* Skip some tests due to non-deterministic behaviour
* Fix test_initialization
* Remove unneccessary initialization of nn.Embedding
* Improve docs
* Fix dummies
* Remove ViTMAEFeatureExtractor from docs
* Add model to README and table of contents
* Delete inference file
* update XLMProphetNet link
* update DPR link
* change prophetnet link
* change link MBART
* change link GPT
* update gpt2 link
* ctrl update link
* update Transformer-XL link
* Update Reformer link
* update xlnet link
* bert update link
* udpate albert link
* roberta update link
* update distilbert link
* update convbert link
* update XLM link
* xlm roberta update link
* update Flaubert link
* update electra link
* update funnel transformer and longformer
* bart update link
* pegasus update link
* udpate marianmt link
* t5 update link
* mt5 update link
* Add ONNX classes to main package
* Remove permalinks from ONNX guide
* Fix ToC entry
* Revert "Add ONNX classes to main package"
This reverts commit eb794a5b00.
* Add ONNX classes to main doc
* Fix syntax highlighting in doc
* Fix text
* Add FeaturesManager to doc
* Use paths to reference ONNX classes
* Add FeaturesManager to init
* Add missing ONNX paths
* Add IBertOnnxConfig and tests
* add all the supported features for IBERT and remove outputs in IbertOnnxConfig
* use OnnxConfig
* fix codestyle
* remove serialization.rst
* codestyle
* Start the work on TFVisionEncoderDecoderModel
* Expose TFVisionEncoderDecoderModel
* fix import
* Add modeling_tf_vision_encoder_decoder to _ignore_modules in get_model_modules()
* reorder
* Apply the fix for checkpoint loading as in #14016
* remove attention_mask + fix VISION_DUMMY_INPUTS
* A minimal change to make TF generate() work for vision models as encoder in encoder-decoder setting
* fix wrong condition: shape_list(input_ids) == 2
* add tests
* use personal TFViTModel checkpoint (for now)
* Add equivalence tests + projection layer
* style
* make sure projection layer can run
* Add examples
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Clean comments (need to work on TODOs for PyTorch models)
* Remove TF -> PT in check_pt_tf_equivalence for TFVisionEncoderDecoderModel
* fixes
* Revert changes in PT code.
* Update tests/test_modeling_tf_vision_encoder_decoder.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add test_inference_coco_en for TF test
* fix quality
* fix name
* build doc
* add main_input_name
* Fix ckpt name in test
* fix diff between master and this PR
* fix doc
* fix style and quality
* fix missing doc
* fix labels handling
* Delete auto.rst
* Add the changes done in #14016
* fix prefix
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* make style
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add FlaxRoFormer
* Clean code + make quality
* Fix output pooling for FlaxRoFormerForMultipleChoiceModule
* Apply suggestions from code review
* add flax model to repos
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix bad examples
* Add black formatting to style_doc
* Use first nonempty line
* Put it at the right place
* Don't add spaces to empty lines
* Better templates
* Deal with triple quotes in docstrings
* Result of style_doc
* Enable mdx treatment and fix code examples in MDXs
* Result of doc styler on doc source files
* Last fixes
* Break copy from
* Add ElectraForCausalLM and cover some basic tests & need to fix a few tests
* Fix bugs
* make style
* make fix-copies
* Update doc
* Change docstring to markdown format
* Remove redundant update_keys_to_ignore
* Pipeline chunks.
* Batching for Chunking pipelines ?
* Batching for `question-answering` and `zero-shot-cls`.
* Fixing for FNet.
* Making ASR a chunk pipeline.
* Chunking ASR API.
* doc style.
* Fixing ASR test.
* Fixing QA eror (p_mask, padding is 1, not 0).
* Enable both vad and simple chunking.
* Max length for vad.
* remove inference mode, crashing on s2t.
* Revert ChunkPipeline for ASRpipeline.
Too many knobs for simple integration within the pipeline, better stick
to external convenience functions instead, more control to be had,
simpler pipeline and also easier to replace with other things later.
* Drop necessity for PT for these.
* Enabling generators.
* Add mic + cleanup.
* Typo.
* Typo2.
* Remove ASR work, it does not belong in this PR anymore.
* Update src/transformers/pipelines/pt_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Update src/transformers/pipelines/zero_shot_classification.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Adding many comments.
* Doc quality.
* `hidden_states` handling.
* Adding doc.
* Bad rebase.
* Autofixing docs.
* Fixing CRITICAL bug in the new Zerocls pipeline.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* First commit to add MarianMT to ONNX
* Now MarianModel.forward() automatically generates decoder_input_ids, like BartModel.forward()
* Adjusted MarianOnnxConfig.inputs and outputs to work with seq2seq-lm feature
* Style fix
* Added support for other features for already supported models
* Partial support for causal and seq2seq models
* Partial support for causal and seq2seq models
* Add default task for MarianMT ONNX
* Remove automatic creation of decoder_input_ids
* Extend inputs and outputs for MarianMT ONNX config
* Add MarianMT to ONNX unit tests
* Refactor
* OnnxSeq2SeqConfigWithPast to support seq2seq models
* Parameterized the onnx tests
* Restored run_mlm.py
* Restored run_mlm.py
* [WIP] BART update
* BART and MBART
* Add past_key_values and fix dummy decoder inputs
Using a sequence length of 1 in generate_dummy_outputs() produces large discrepancies, presumably due to some hidden optimisations.
* Refactor MarianOnnxConfig to remove custom past_key_values logic
* Fix quality
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Refactor Marian export to account for base changes
* Fix copies
* Implemented suggestions
* Extend support for causal LM
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Implemented suggestions
* Fixed __init__ to resolve conflict with master
* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"
This reverts commit 0f4e39c559.
* is_torch_available test to avoid failing imports
* sorting parameterize parameters to solve ERROR gw0 gw1
* tests fix
* tests fix
* GPT2 with past fix
* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially
* Removed onnx file
* Implemented suggestions
* Fixed __init__ to resolve conflict with master
* Remove commented import
* Remove ONNX model
* Remove redundant class method
* Tidy up imports
* Fix quality
* Refactor dummy input function
* Add copied from statements to Marian config functions
* Remove false copied from comments
* Fix copy from comment
Co-authored-by: Massimiliano Bruni <massimiliano.bruni@hcl.com>
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>
* PoC for conserving old links
* Do the same for other links
* remap the redirects section
* add instructions on how to move sections
* improve
Co-authored-by: Stas Bekman <stas@stason.org>
* Test workflow
* Build doc
* Make a clean build
* Add doc config
* Restore other workflows
* Final job
* Print something in else statements
* Pull before making changes
* Convert a few docs
* And another
* Last tutorials
* New syntax for colab links
* Convert a few docs
* And another
* Last tutorials
* New syntax for colab links
* First draft
* Style and remove mlm
* Make forward pass work
* More improvements
* More improvements
* Fix bug
* More improvements
* More improvements
* Add PerceiverTokenizer first draft
* Improve conversion script
* More improvements
* Make conversion script work for the encoder
* Make conversion script work with local pickle files
* Style & quality, fix-copies
* Add dummy input to conversion script
* Add absolute position embeddings to TextPreProcessor
* Make forward pass of encoder work
* More improvements
* Move text preprocessor to separate script
* More improvements
* More improvements
* Add post processor
* Make MLM model work
* Style
* Add PerceiverForMaskedLM
* Add PerceiverImagePreprocessor
* Make style
* Make PerceiverForImageClassification work
* More improvements
* More improvements
* Use tokenizer in conversion script
* Use PerceiverForMaskedLM in conversion script
* Define custom PerceiverModelOutput
* Improve PerceiverAttention to make it work for both MLM and image classification
* More improvements
* More improvements
* More improvements to the conversion script
* Make conversion script work for both MLM and image classification
* Add PerceiverFeatureExtractor
* More improvements
* Style and quality
* Add center cropping
* Fix bug
* Small fix
* Add print statement
* Fix bug in image preprocessor
* Fix bug with conversion script
* Make output position embeddings an nn.Parameter layer instead of nn.Embedding
* Comment out print statements
* Add position encoding classes
* More improvements
* Use position_encoding_kwargs
* Add PerceiverForImageClassificationFourier
* Make style & quality
* Add PerceiverForImageClassificationConvProcessing
* Style & quality
* Add flow model
* Move processors to modeling file
* Make position encodings modular
* Make basic decoder use modular position encodings
* Add PerceiverForOpticalFlow to conversion script
* Add AudioPreprocessor
* Make it possible for the basic decoder to use Fourier position embeddings
* Add PerceiverForMultimodalAutoencoding
* Improve model for optical flow
* Improve _build_network_inputs method
* Add print statement
* Fix device issue
* Fix device of Fourier embeddings
* Add print statements for debugging
* Add another print statement
* Add another print statement
* Add another print statement
* Add another print statement
* Improve PerceiverAudioPreprocessor
* Improve conversion script for multimodal modal
* More improvements
* More improvements
* Improve multimodal model
* Make forward pass multimodal model work
* More improvements
* Improve tests
* Fix some more tests
* Add output dataclasses
* Make more tests pass
* Add print statements for debuggin
* Add tests for image classification
* Add PerceiverClassifierOutput
* More improvements
* Make more tests pass for the optical flow model
* Make style & quality
* Small improvements
* Don't support training for optical flow model for now
* Fix _prepare_for_class for tests
* Make more tests pass, add some docs
* Add multimodal model to tests
* Minor fixes
* Fix tests
* Improve conversion script
* Make fixup
* Remove pos_dim argument
* Fix device issue
* Potential fix for OOM
* Revert previous commit
* Fix test_initialization
* Add print statements for debugging
* Fix print statement
* Add print statement
* Add print statement
* Add print statement
* Add print statement
* Add print statement
* Add print statement
* Remove need for output_shape
* Comment out output_shape
* Remove unnecessary code
* Improve docs
* Fix make fixup
* Remove PerceiverTextProcessor from init
* Improve docs
* Small improvement
* Apply first batch of suggestions from code review
* Apply more suggestions from code review
* Update docstrings
* Define dicts beforehand for readability
* Rename task to architecture in conversion script, include PerceiverModel in tests
* Add print statements for debugging
* Fix tests on GPU
* Remove preprocessors, postprocessors and decoders from main init
* Add integration test
* Fix docs
* Replace einops by torch
* Update for new docs frontend
* Rename PerceiverForImageClassification
* Improve docs
* Improve docs
* Improve docs of PerceiverModel
* Fix some more tests
* Improve center_crop
* Add PerceiverForSequenceClassification
* Small improvements
* Fix tests
* Add integration test for optical flow model
* Clean up
* Add tests for tokenizer
* Fix tokenizer by adding special tokens properly
* Fix CI
* up
* up
* up
* make it cleaner
* correct
* make styhahalal
* add more tests
* finish
* small fix
* make style
* up
* tryout to solve cicrle ci
* up
* fix more tests
* fix more tests
* apply sylvains suggestions
* fix import
* correct docs
* add pyctcdecode only to speech tests
* fix more tests
* add tf, flax and pt tests
* add pt
* fix last tests
* fix more tests
* Apply suggestions from code review
* change lines
* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
* correct tests
* correct tests
* add doc string
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
* implement MLukeTokenizer and LukeForMaskedLM
* update tests
* update docs
* add LukeForMaskedLM to check_repo.py
* update README
* fix test and specify the entity pad id in tokenization_(m)luke
* fix EntityPredictionHeadTransform
* Make DefaultDataCollator importable from root
* Add documentation for DefaultDataCollator and add return_tensors argument to all class docstrings
* make style
* Add DefaultDataCollator to data_collator.rst
* Add DefaultDataCollator to data_collator.rst
