* properly support Sequence of pretokenizers
* actual fix
* make sure the fix works. Tests are not working for sure!
* hacky way
* add TODO
* update
* add a todo
* nits
* rename test
* nits
* rename test
* add: NumberNormalizer works for integers, floats, common currencies, negative numbers and percentages
* fix: renamed number normalizer class and added normalization to SpeechT5Processor
* fix: restyled with black and ruff, should pass code quality tests
* fix: moved normalization to tokenizer and other small changes to normalizer
* add: test for normalization and changed the existing full tokenizer test
* fix: tokenization tests now pass, made changes to existing tokenization where normalization is covered; added normalize arg to func signature
* fix: changed default normalize setting to False, modified the tests a bit
* fix: added support for comma separated numbers, tokenization on the fly with kwargs and normalizer getter setter funcs
* init commit
* config updated also some modeling
* Processor and Model config combined
* extraction pipeline(upto before spectogram & mel_conditioner) added but not properly tested
* model loading successful!
* feature extractor done!
* FE can now be called from HF
* postprocessing added in fe file
* same as prev commit
* Pop2PianoConfig doc done
* cfg docs slightly changed
* fe docs done
* batched
* batched working!
* temp
* v1
* checking
* trying to go with generate
* with generate and model tests passed
* before rebasing
* .
* tests done docs done remaining others & nits
* nits
* LogMelSpectogram shifted to FeatureExtractor
* is_tf rmeoved from pop2piano/init
* import solved
* tokenization tests added
* minor fixed regarding modeling_pop2piano
* tokenizer changed to only return midi_object and other changes
* Updated paper abstract(Camera-ready version) (#2)
* more comments and nits
* ruff changes
* code quality fix
* sg comments
* t5 change added and rebased
* comments except batching
* batching done
* comments
* small doc fix
* example removed from modeling
* ckpt
* forward it compatible with fe and generation done
* comments
* comments
* code-quality fix(maybe)
* ckpts changed
* doc file changed from mdx to md
* test fixes
* tokenizer test fix
* changes
* nits done main changes remaining
* code modified
* Pop2PianoProcessor added with tests
* other comments
* added Pop2PianoProcessor to dummy_objects
* added require_onnx to modeling file
* changes
* update .md file
* remove extra line in index.md
* back to the main index
* added pop2piano to index
* Added tokenizer.__call__ with valid args and batch_decode and aligned the processor part too
* changes
* added return types to 2 tokenizer methods
* the PR build test might work now
* added backends
* PR build fix
* vocab added
* comments
* refactored vocab into 1 file
* added conversion script
* comments
* essentia version changed in .md
* comments
* more tokenizer tests added
* minor fix
* tests extended for outputs acc check
* small fix
---------
Co-authored-by: Jongho Choi <sweetcocoa@snu.ac.kr>
* a draft version
* v2 integration
* fix
* make it more generic and works for IA3
* add set adapter and multiple adapters support
* fixup
* adapt a bit
* oops
* oops
* oops
* adapt more
* fix
* add more refactor
* now works with model class
* change it to instance method as it causes issues with `jit`.
* add CR
* change method name
* add `add_adapter` method
* clean up
* Update src/transformers/adapters/peft_mixin.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add moe utils
* fixup
* Update src/transformers/adapters/peft_mixin.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* adapt
* oops
* fixup
* add is_peft_available
* remove `requires_backend`
* trainer compatibility
* fixup + docstring
* more details
* trigger CI
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_utils.py
* fixup + is_main_process
* added `save_peft_format` in save_pretrained
* up
* fix nits here and there
* nits here and there.
* docs
* revert `encoding="utf-8"`
* comment
* added slow tests before the PEFT release.
* fixup and nits
* let's be on the safe zone
* added more comments
* v1 docs
* add remaining docs
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* move to `lib_integrations`
* fixup
* this time fixup
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* address final comments
* refactor to use `token`
* add PEFT to DockerFile for slow tests.
* added pipeline support.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* properly support Sequence of pretokenizers
* actual fix
* make sure the fix works. Tests are not working for sure!
* hacky way
* add TODO
* update
* add a todo
* draft changes
* update and add tests
* styling for no
* move test
* path to usable model
* update test
* small update
* update bertbased tokenizers
* don'tuse kwargs for _tokenize
* don'tuse kwargs for _tokenize
* fix copies
* update
* update test for special tokenizers
* fixup
* skip two tests
* remove pdb breakpiont()
* wowo
* rewrite custom tests
* nits
* revert chang in target keys
* fix markup lm
* update documentation of the argument
* Replaces calls to `.cuda` with `.to(torch_device)` in tests
`torch.Tensor.cuda()` is a pre-0.4 solution to changing a tensor's device. It is recommended to prefer `.to(...)` for greater flexibility and error handling. Furthermore, this makes it more consistent with other tests (that tend to use `.to(torch_device)`) and ensures the correct device backend is used (if `torch_device` is neither `cpu` or `cuda`).
* addressing review comments
* more formatting changes in Bloom test
* `make style`
* Update tests/models/bloom/test_modeling_bloom.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixes style failures
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* added more details about flash attention
* correct and add more details
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* few modifs
* more details
* up
* Apply suggestions from code review
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
* adapt from suggestion
* Apply suggestions from code review
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
* trigger CI
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix nits and copies
* add new section
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
* Suggestions on Pipeline_webserver
docs: reorder the warning tip for pseudo-code
Co-Authored-By: Wonhyeong Seo <wonhseo@kakao.com>
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/ko/pipeline_webserver.md
Co-authored-by: Wonhyeong Seo <wonhseo@kakao.com>
---------
Co-authored-by: Wonhyeong Seo <wonhseo@kakao.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* add AutoModelForTextToSpeech class
* add TTS pipeline and tessting
* add docstrings to text_to_speech pipeline
* fix torch dependency
* corrector 'processor is None' case in Pipeline
* correct repo id
* modify text-to-speech -> text-to-audio
* remove processor
* rename text_to_speech pipelines files to text_audio
* add textToWaveform and textToSpectrogram instead of textToAudio classes
* update TTS pipeline to the bare minimum
* update tests TTS pipeline
* make style and erase useless import torch in TTS pipeline tests
* modify how to check if generate or forward in TTS pipeline
* remove unnecessary extra new lines
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* refactor input_texts -> text_inputs
* correct docstrings of TTS.__call__
* correct the shape of generated waveform
* take care of Bark tokenizer special case
* correct run_pipeline_test TTS
* make style
* update TTS docstrings
* address Sylvain nit refactors
* make style
* refactor into one liners
* correct squeeze
* correct way to test if forward or generate
* Update output audio waveform shape
* make style
* correct import
* modify how the TTS pipeline test if a model can generate
* align shape output of TTS pipeline with consistent shape
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* add util for ram efficient loading of model when using fsdp
* make fix-copies
* fixes 😅
* docs
* making it further easier to use
* rename the function
* refactor to handle fsdp ram efficiency in `from_pretrained`
* fixes
* fixes
* fixes
* update
* fixes
* revert `load_pretrained_model_only_on_rank0`
* resolve `load_from_checkpoint`
* Inconsistency in PreTrainedModel.resize_token_embeddings
This PR addresses https://github.com/huggingface/transformers/issues/25241.
In previous implementation when ZeRO stage 3 was enbaled, resize_token_embeddings would create independent PyTorch weights on each device. Here we ensure that new embeddings are created with DeepSpeed init, and are properly partitioned accros devices.
* formatting with black
* adding the removed comments back in
---------
Co-authored-by: Sina Moeini <smoeini@amazon.com>
* fix EVERYTHING
* more fixes
* ⚗️⚗️ Tokenizer magic ⚗️⚗️
* wrong value but test passes for the TODO
* update
* updat
* safe protobuf import?
* style
* non gated repo
* update
* fixup
* Update src/transformers/models/llama/tokenization_llama.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/llama/tokenization_llama.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/t5/test_tokenization_t5.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* nits
* fix t5 too
* use assert equal
* fix llama decoding
* nits on t5
* fixup
* only remove the prefix space, not other spaces
* more deconding tests and more todos
* fix CI as well
* fixup
* skip failing test on CI (its tf its ok)
* skip test_subword_regularization_tokenizer that is also crashing on the CI for TF
* update llama
* revert good fixes
* fixup
* empty
* explain why we need to encode with an additional token
* better warning?
* nits
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix
* revert cahnges and update resizing of embedding layer
* use wraning
* fixup
* more styling nits
* fix all tests that overload the embedding tests
* 👀👀 remove breakpoint
* remove useless overload + overload correctly where needed
* resize lm head with new vocab size
* reverse not necessary changes
* style
* fix CIs!
* fix last CI tests, adapt bark and Marian
* fixup
* Adds `TRANSFORMERS_TEST_DEVICE`
Mirrors the same API in the diffusers library. Useful in transformers
too.
* replace backend checking with trying `torch.device`
* Adds better error message for unknown test devices
* `make style`
* adds documentation showing `TRANSFORMERS_TEST_DEVICE` usage.
