* Adding warning messages to BERT for missing attention masks
These warning messages when there are pad tokens within the input ids and
no attention masks are given. The warning message should only show up once.
* Adding warning messages to BERT for missing attention masks
These warning messages are shown when the pad_token_id is not None
and no attention masks are given. The warning message should only
show up once.
* Ran fix copies to copy over the changes to some of the other models
* Add logger.warning_once.cache_clear() to the test
* Shows warning when there are no attention masks and input_ids start/end with pad tokens
* Using warning_once() instead and fix indexing in input_ids check
---------
Co-authored-by: JB Lau <hckyn@voyager2.local>
* don't add space before single letter chars that don't have a merge
* fix the fix
* fixup
* add a test
* more testing
* fixup
* hack to make sure fast is also fixed
* update switch transformers test
* revert convert slow
* Update src/transformers/models/t5/tokenization_t5.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add typechecking
* quality
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Preliminary work on some models
* Fix test load missing and make sure nonpersistent buffers are tested
* Always ignore nonpersistent buffers if in state_dict
* Treat models
* More models
* Treat remaining models
* Fix quality
* Fix tests
* Remove draft
* This test is not needed anymore
* Fix copies
* Fix last test
* Newly added models
* Fix last tests
* Address review comments
* Fix TypeError: Object of type int64 is not JSON serializable
* Convert numpy.float64 and numpy.int64 to float and int for json serialization
* Black reformatted examples/pytorch/token-classification/run_ner_no_trainer.py
* * make style
* Squash 88 commits
* Use markdown
* Remove mdx files due to bad rebase
* Fix modeling files due to bad rebase
* Fix style
* Update comment
* fix
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Allow dict input for audio classification pipeline
* make style
* Empty commit to trigger CI
* Empty commit to trigger CI
* check for torchaudio
* add pip instructions
Co-authored-by: Sylvain <sylvain.gugger@gmail.com>
* Update src/transformers/pipelines/audio_classification.py
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
* asr -> audio class
* asr -> audio class
---------
Co-authored-by: Sylvain <sylvain.gugger@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
* Replace python random with torch.rand to enable dynamo.export
* revert changes to flax model code
* Remove unused random import
* Fix torch template
* Move torch.manual_seed(0) to right location
* Refactor hyperparameter search backends
* Simpler refactoring without abstract base class
* black
* review comments:
specify name in class
use methods instead of callable class attributes
name constant better
* review comments: safer bool checking, log multiple available backends
* test ALL_HYPERPARAMETER_SEARCH_BACKENDS vs HPSearchBackend in unit test, not module. format with black.
* copyright
* let's go!
* initial implementation of token-level timestamps
* only return a single timestamp per token
* remove token probabilities
* fix return type
* fix doc comment
* strip special tokens
* rename
* revert to not stripping special tokens
* only support models that have alignment_heads
* add integration test
* consistently name it token-level timestamps
* small DTW tweak
* initial support for ASR pipeline
* fix pipeline doc comments
* resolve token timestamps in pipeline with chunking
* change warning when no final timestamp is found
* return word-level timestamps
* fixup
* fix bug that skipped final word in each chunk
* fix failing unit tests
* merge punctuations into the words
* also return word tokens
* also return token indices
* add (failing) unit test for combine_tokens_into_words
* make combine_tokens_into_words private
* restore OpenAI's punctuation rules
* add pipeline tests
* make requested changes
* PR review changes
* fix failing pipeline test
* small stuff from PR
* only return words and their timestamps, not segments
* move alignment_heads into generation config
* forgot to set alignment_heads in pipeline tests
* tiny comment fix
* grr
* Fix saved_model_creation_extended
* Skip the BLIP model creation test for now
* Fix TF SAM test
* Fix longformer tests
* Fix Wav2Vec2
* Add a skip for XLNet
* make fixup
* make fix-copies
* Add comments
* Add test for proper input signatures
* No more signature pruning
* Test the dummy inputs are valid too
* fine-tine -> fine-tune
* Fix indent in test_dataset_conversion
* Use tied weight keys
* More
* Fix tied weight missing warning
* Only give info on unexpected keys with different classes
* Deal with empty archs
* Fix tests
* Refine test
* Fix one BLIP arg not being optional, remove misspelled arg
* Remove the lxmert test overrides and just use the base test_saved_model_creation
* saved_model_creation fixes and re-enabling tests across the board
* Remove unnecessary skip
* Stop caching sinusoidal embeddings in speech_to_text
* Fix transfo_xl compilation
* Fix transfo_xl compilation
* Fix the conditionals in xglm
* Set the save spec only when building
* Clarify comment
* Move comment correctly
* Correct embeddings generation for speech2text
* Mark RAG generation tests as @slow
* Remove redundant else:
* Add comment to clarify the save_spec line in build()
* Fix size tests for XGLM at last!
* make fixup
* Remove one band_part operation
* Mark test_keras_fit as @slow
* Revert whisper change and modify the test_compile_tf_model test
* make fixup
* Tweak test slightly
* Add functional model saving to test
* Ensure TF can infer shapes for data2vec
* Add override for efficientformer
* Mark test as slow