* add dia model
* add tokenizer files
* cleanup some stuff
* brut copy paste code
* rough cleanup of the modeling code
* nuke some stuff
* more nuking
* more cleanups
* updates
* add mulitLayerEmbedding vectorization
* nits
* more modeling simplifications
* updates
* update rope
* update rope
* just fixup
* update configuration files
* more cleanup!
* default config values
* update
* forgotten comma
* another comma!
* update, more cleanups
* just more nits
* more config cleanups
* time for the encoder
* fix
* sa=mall nit
* nits
* n
* refacto a bit
* cleanup
* update cv scipt
* fix last issues
* fix last nits
* styling
* small fixes
* just run 1 generation
* fixes
* nits
* fix conversion
* fix
* more fixes
* full generate
* ouf!
* fixes!
* updates
* fix
* fix cvrt
* fixup
* nits
* delete wrong test
* update
* update
* test tokenization
* let's start changing things bit by bit - fix encoder step
* removing custom generation, moving to GenerationMixin
* add encoder decoder attention masks for generation
* mask changes, correctness checked against ad29837 in dia repo
* refactor a bit already --> next cache
* too important not to push :)
* minimal cleanup + more todos
* make main overwrite modeling utils
* add cfg filter & eos filter
* add eos countdown & delay pattern
* update eos countdown
* add max step eos countdown
* fix tests
* fix some things
* fix generation with testing
* move cfg & eos stuff to logits processor
* make RepetitionPenaltyLogitsProcessor flexible
- can accept 3D scores like (batch_size, channel, vocab)
* fix input_ids concatenation dimension in GenerationMixin for flexibility
* Add DiaHangoverLogitsProcessor and DiaExponentialDecayLengthPenalty classes; refactor logits processing in DiaForConditionalGeneration to utilize new configurations and improve flexibility.
* Add stopping criteria
* refactor
* move delay pattern from processor to modeling like musicgen.
- add docs
- change eos countdown to eos delay pattern
* fix processor & fix tests
* refactor types
* refactor imports
* format code
* fix docstring to pass ci
* add docstring to DiaConfig & add DiaModel to test
* fix docstring
* add docstring
* fix some bugs
* check
* porting / merging results from other branch - IMPORTANT: it very likely breaks generation, the goal is to have a proper forward path first
* experimental testing of left padding for first channel
* whoops
* Fix merge to make generation work
* fix cfg filter
* add position ids
* add todos, break things
* revert changes to generation --> we will force 2d but go 3d on custom stuff
* refactor a lot, change prepare decoder ids to work with left padding (needs testing), add todos
* some first fixes to get to 10. in generation
* some more generation fixes / adjustment
* style + rope fixes
* move cfg out, simplify a few things, more todos
* nit
* start working on custom logit processors
* nit
* quick fixes
* cfg top k
* more refactor of logits processing, needs a decision if gen config gets the new attributes or if we move it to config or similar
* lets keep changes to core code minimal, only eos scaling is questionable atm
* simpler eos delay logits processor
* that was for debugging :D
* proof of concept rope
* small fix on device mismatch
* cfg fixes + delay logits max len
* transformers rope
* modular dia
* more cleanup
* keep modeling consistently 3D, generate handles 2D internally
* decoder starts with bos if nothing
* post processing prototype
* style
* lol
* force sample / greedy + fixes on padding
* style
* fixup tokenization
* nits
* revert
* start working on dia tests
* fix a lot of tests
* more test fixes
* nit
* more test fixes + some features to simplify code more
* more cleanup
* forgot that one
* autodocs
* small consistency fixes
* fix regression
* small fixes
* dia feature extraction
* docs
* wip processor
* fix processor order
* processing goes brrr
* transpose before
* small fix
* fix major bug but needs now a closer look into the custom processors esp cfg
* small thing on logits
* nits
* simplify indices and shifts
* add simpler version of padding tests back (temporarily)
* add logit processor tests
* starting tests on processor
* fix mask application during generation
* some fixes on the weights conversion
* style + fixup logits order
* simplify conversion
* nit
* remove padding tests
* nits on modeling
* hmm
* fix tests
* trigger
* probably gonna be reverted, just a quick design around audio tokenizer
* fixup typing
* post merge + more typing
* initial design for audio tokenizer
* more design changes
* nit
* more processor tests and style related things
* add to init
* protect import
* not sure why tbh
* add another protect
* more fixes
* wow
* it aint stopping :D
* another missed type issue
* ...
* change design around audio tokenizer to prioritize init and go for auto - in regards to the review
* change to new causal mask function + docstrings
* change ternary
* docs
* remove todo, i dont think its essential tbh
* remove pipeline as current pipelines do not fit in the current scheme, same as csm
* closer to wrapping up the processor
* text to audio, just for demo purposes (will likely be reverted)
* check if it's this
* save audio function
* ensure no grad
* fixes on prefixed audio, hop length is used via preprocess dac, device fixes
* integration tests (tested locally on a100) + some processor utils / fixes
* style
* nits
* another round of smaller things
* docs + some fixes (generate one might be big)
* msytery solved
* small fix on conversion
* add abstract audio tokenizer, change init check to abstract class
* nits
* update docs + fix some processing :D
* change inheritance scheme for audio tokenizer
* delete dead / unnecessary code in copied generate loop
* last nits on new pipeline behavior (+ todo on tests) + style
* trigger
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Vasqu <antonprogamer@gmail.com>
* fix XPU UT error case brough by RNG difference btw XPU and CUDA
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* enable tests/models/llama/test_modeling_llama.py::LlamaIntegrationTest::test_model_7b_logits and tests/models/llama/test_modeling_llama.py::LlamaIntegrationTest::test_model_7b_logits_bf16 on xpu
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* Revert "enable tests/models/llama/test_modeling_llama.py::LlamaIntegrationTest::test_model_7b_logits and tests/models/llama/test_modeling_llama.py::LlamaIntegrationTest::test_model_7b_logits_bf16 on xpu"
This reverts commit 3ef83a4f02.
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* use torch.testing.assertclose instead to get more details about error in cis
* fix
* style
* test_all
* revert for I bert
* fixes and updates
* more image processing fixes
* more image processors
* fix mamba and co
* style
* less strick
* ok I won't be strict
* skip and be done
* up
* Add SynthIDTextWatermarkLogitsProcessor
* esolving comments.
* Resolving comments.
* esolving commits,
* Improving SynthIDWatermark tests.
* switch to PT version
* detector as pretrained model + style
* update training + style
* rebase
* Update logits_process.py
* Improving SynthIDWatermark tests.
* Shift detector training to wikitext negatives and stabilize with lower learning rate.
* Clean up.
* in for 7B
* cleanup
* upport python 3.8.
* README and final cleanup.
* HF Hub upload and initiaze.
* Update requirements for synthid_text.
* Adding SynthIDTextWatermarkDetector.
* Detector testing.
* Documentation changes.
* Copyrights fix.
* Fix detector api.
* ironing out errors
* ironing out errors
* training checks
* make fixup and make fix-copies
* docstrings and add to docs
* copyright
* BC
* test docstrings
* move import
* protect type hints
* top level imports
* watermarking example
* direct imports
* tpr fpr meaning
* process_kwargs
* SynthIDTextWatermarkingConfig docstring
* assert -> exception
* example updates
* no immutable dict (cant be serialized)
* pack fn
* einsum equivalent
* import order
* fix test on gpu
* add detector example
---------
Co-authored-by: Sumedh Ghaisas <sumedhg@google.com>
Co-authored-by: Marc Sun <marc@huggingface.co>
Co-authored-by: sumedhghaisas2 <138781311+sumedhghaisas2@users.noreply.github.com>
Co-authored-by: raushan <raushan@huggingface.co>
* add early stopping logits processor
* black formmated
* indent
* follow method signature
* actual logic
* check for None
* address comments on docstrings and method signature
* add unit test under `LogitsProcessorTest` wip
* unit test passing
* black formatted
* condition per sample
* add to BarkModelIntegrationTests
* wip BarkSemanticModelTest
* rename and add to kwargs handling
* not add to BarkSemanticModelTest
* correct logic and assert last outputs tokens different in test
* doc-builder style
* read from kwargs as well
* assert len of with less than that of without
* ruff
* add back seed and test case
* add original impl default suggestion
* doc-builder
* rename and use softmax
* switch back to LogitsProcessor and update docs wording
* camelCase and spelling and saving compute
* assert strictly less than
* assert less than
* expand test_generate_semantic_early_stop instead
* Fix issues in test_exponential_decay_length_penalty
Fix tests which were broken and add validation of negative scores.
Current test didn't take into account that ExponentialDecayLengthPenalty updates the score inplace, resulting in updates to base tested Tensor.
In addition, the gt assert had empty Tensors due to indexing along the batch dimension.
Test is currently expected to fail to show ExponentialDecayLengthPenalty issues with negative scores
* Fix ExponentialDecayLengthPenalty negative logits issue
In cases where the scores are negative, ExponentialDecayLengthPenalty decreases the score of eos_token_id instead of increasing it.
To fix this issue we compute the penalty of the absolute value and add it to the original score.
* Add examples for ExponentialDecayLengthPenalty
* Fix styling issue in ExponentialDecayLengthPenalty doc
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Style and quality fix
* Fix example outputs
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Add epsilon- and eta-sampling.
Add epsilon- and eta-sampling, following the official code from https://github.com/john-hewitt/truncation-sampling and adapting to be more configurable, as required by Huggingface transformers.
* Add unit tests for epsilon- and eta-sampling.
* Black: fix code formatting.
* Fix docstring spacing.
* Clean up newlines.
* Fix implementation bugs and their associated tests.
* Remove epsilon- and eta-sampling parameters from PretrainedConfig.
* Clarify and clean up the documentation.
* Remove parameters for PretrainedConfig test.
* move generation_*.py src files into generation/*.py
* populate generation.__init__ with lazy loading
* move imports and references from generation.xxx.object to generation.object
