* Add ImageProcessorFast to BiT processor
* propose a fast processor and add tests
* all tests pass except one
* run make
* remove useless print
* use same test as clip
* apply make
* Update src/transformers/models/bit/image_processing_bit_fast.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* Update setup.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* Update src/transformers/models/bit/image_processing_bit_fast.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* apply review comment
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Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* fix BlockMask handling when using flex_attention for llama/mistral/gemma2
* fix attention_mask types
* revert type hints and fixup
* remove unnecessary assertion
* support fast image processor layoutlmv3
* make style
* add warning and update test
* make style
* Update src/transformers/models/layoutlmv3/image_processing_layoutlmv3_fast.py
* Update image_processing_auto.py
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Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* support flava fast image processor
* run style and quality
* update test
* update according to reviews
* make style
* update comment on BICUBIC
* make style
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Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* add test and fast image processor
* make style
* Update src/transformers/models/perceiver/image_processing_perceiver_fast.py
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* make style
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Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* First pass at speech granite
Add encoder / projector, rename things
* Combine into one model file with causal lm outputs for forward
* Add loss calc
* Fix config loading
Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com>
* Split new / old loading logic
* Use transformers integration for loading peft adapters
* Add generation wrapper for selective lora enablement
* Add note for qformer encoder automodel
* Guard torch/audio imports in feature extractor
* Handle granite speech autoclasses
* Handle optional deps in package structure for granite speech
* Add granite pretrained model def for init
* Add dummy objects for torch/torchaudio
* Add tests for granite speech processor
* Minor formatting fixes and refactoring
* Add options for falling back to config in forward
* Tentative model docstrings for granite speech
* Fix config type
* Remove legacy load
* Allow non-lora variants for granite speech
* Override weight tying for llm
* Use text config instead of llm config
* Add output embeddings getter to fix weight tying
* Fix relative imports
* computing the number of audio features, based on the raw audio sequence.
* collating audio inputs, and keeping the original lengths.
* asserted we have text. otherwise we can't specify the audio special token.
* assering the number of audio-symbols/audios match correctly.
running get validated_audios only when audio is present
* indentation bugfix + supporting different feature lengths when expanding audio.
* redundant, done in _get_validated_text
* adapting the tests:
- we must have text (not either audio or text)
- _get_num_audio_features takes a list of raw lengths, provided it insetad.
* Minor cleanup, remove unused import
* Add more tests for batch feature processing
* Allow setting offset in rel position embeddings
* Add config option for warning if peft is not installed w/ lora
* Port blip2 qformer code into granite speech
* Add sad test for numpy arr processing
* Allow numpy arrays / tuples in granite speech processor
* Fix config type for projector
* - pad instead of creating a zeros tensor, to keep the original dtype/device (support bfloat16)
- cast input_features to the model dtype (support bfloat16)
* merge Blip2QFormerConfig to GraniteSpeechProjectorConfig
* prevent a crash when re-saving/loading the model (line 109)
* consider additional edge cases during preprocessing.
* consider additional edge cases during preprocessing.
* add features mask for batched inference (bugfix)
* Minor refactor, remove multiaudio processor tests
* Add set input/output embeddings for granite speech
* Fix feature dim check in processor test
* Pop input features in embed test for granite speech
* Small fixes for test edge cases
Add granite speech to seq2seq causal lm mapping names
* Add small tests for granite speech model
* Fix data parallelism test
* Standardize model class names
* Fix check for copies
* Fix misaligned init check
* Skip granite speech in checkpoint check
* Use default for tie_word_embeddings in granite speech
* Fix non documentation granite speech repo issues
* Fix comments and docstring checks
* Add placeholder docs for granite speech
* Fix test naming collision
* Code formatting
* Rerun torch dummy obj regen
* Fix save pretrained for granite speech
* Import sorting
* Fix tests typo
* Remove offset hack
* Pass args through encoder config
* Remove unused prune heads from blip2
* removing einsum. replaced with explicit multiplication (relative positional encodings) and sdpa attention.
* remove Sequential from ConformerFeedForward and ConformerConvModule. + fix for sdpa attention
* remove GraniteSpeechConformerScale
* rename to hidden_states
* rename conformer layers to self.layers, remove the first linear from the list to keep the list homogenous.
* move pre-norm to the attention/feedforward blocks (avoid complex module wrapping)
* adding pre_norm into forward
* feature extractor refactoring to resemble how it's done in phi4multimodal.
* rename feature_extractor to audio_processor
* bugfix: input_feature_mask fix to get the exact number tokens.
* Fix pytest decorator in processor test
* Add (disabled) integration tests for granite speech
* Fix handling of optional feature masking
* Loosen validation in processing for vLLM compatability
* Formatting fixes
* Update init structure to mirror llama
* Make granite speech projector generic
* Update test config to reflect generic projector
* Formatting fixes
* Fix typos, add license
* Fix undefined var in input processing
* Cleanup and expose ctc encoder
* Add missing config docstrings
* Better var names, type hints, etc
* Set attn context size in init
* Add max pos emb to encoder config
* Cleanup feature extractor
* Add granite speech architecture details
* Remove granite speech qformer ref
* Add paper link, explicit calc for qkv
* Calculate padding directly in depthwise conv1d init
* Raise value error instead of asserting
* Reorder class defs (classes used at top)
* Precompute relpos distances
* Run formatting
* Pass attention distances through forward
* Apply suggestions from code review
Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com>
* Add todo for using common batch feature extraction
* Rename audios/features
* Ensure chat template may be provided to processor
* Move granite speech docs to audio models
* Add todos for input proc refactoring
* Fix import order
* Guard torch import
* Use relative imports
* Require torch backend for processor in granite speech
* Add backend guards in feature extractor
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Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com>
Co-authored-by: Avihu Dekel <avihu.dekel@ibm.com>
Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com>
* Add saving in the new format (but no loading yet!)
* Add saving in the new format (but no loading yet!)
* A new approach to template files!
* make fixup
* make fixup, set correct dir
* Some progress but need to rework for cached_file
* Rework loading handling again
* Small fixes
* Looks like it's working now!
* make fixup
* Working!
* make fixup
* make fixup
* Add TODO so I don't miss it
* Cleaner control flow with one less indent
* Copy the new logic to processing_utils as well
* Proper support for dicts of templates
* make fixup
* define the file/dir names in a single place
* Update the processor chat template reload test as well
* Add processor loading of multiple templates
* Flatten correctly to match tokenizers
* Better support when files are empty sometimes
* Stop creating those empty templates
* Revert changes now we don't have empty templates
* Revert changes now we don't have empty templates
* Don't support separate template files on the legacy path
* Rework/simplify loading code
* Make sure it's always a chat_template key in chat_template.json
* Update processor handling of multiple templates
* Add a full save-loading test to the tokenizer tests as well
* Correct un-flattening
* New test was incorrect
* Correct error/offline handling
* Better exception handling
* More error handling cleanup
* Add skips for test failing on main
* Reorder to fix errors
* make fixup
* clarify legacy processor file docs and location
* Update src/transformers/processing_utils.py
Co-authored-by: Lucain <lucainp@gmail.com>
* Update src/transformers/processing_utils.py
Co-authored-by: Lucain <lucainp@gmail.com>
* Update src/transformers/processing_utils.py
Co-authored-by: Lucain <lucainp@gmail.com>
* Update src/transformers/processing_utils.py
Co-authored-by: Lucain <lucainp@gmail.com>
* Rename to _jinja and _legacy
* Stop saving multiple templates in the legacy format
* Cleanup the processing code
* Cleanup the processing code more
* make fixup
* make fixup
* correct reformatting
* Use correct dir name
* Fix import location
* Use save_jinja_files instead of save_raw_chat_template_files
* Correct the test for saving multiple processor templates
* Fix type hint
* Update src/transformers/utils/hub.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>
* Patch llava_onevision test
* Update src/transformers/processing_utils.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>
* Refactor chat template saving out into a separate function
* Update tests for the new default
* Don't do chat template saving logic when chat template isn't there
* Ensure save_jinja_files is propagated to tokenizer correctly
* Trigger tests
* Update more tests to new default
* Trigger tests
---------
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Julien Chaumond <julien@huggingface.co>
* the fix that did not get in
* add kernels
* full graph does not work
* simpler is better
* Update src/transformers/integrations/hub_kernels.py
Co-authored-by: Daniël de Kok <me@danieldk.eu>
* Update src/transformers/integrations/fbgemm_fp8.py
Co-authored-by: Daniël de Kok <me@danieldk.eu>
* Update src/transformers/integrations/hub_kernels.py
Co-authored-by: Daniël de Kok <me@danieldk.eu>
* fixup
---------
Co-authored-by: Daniël de Kok <me@danieldk.eu>
Corrects the file path used to locate the CUDA kernels
for the Deformable Attention module. This ensures that
the kernels are loaded correctly, resolving potential
errors during module initialization and usage.
Previously, the identity function was used for dropped tokens
with a weight from the expert that was not applied to the hidden states.
This was misleading, because dropping means, the expert weight is zero.
Instead of trying to fix the weight, we take an easier approach by initializing with zeros.
Fixes issue https://github.com/huggingface/transformers/issues/37017
