* 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
---------
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>
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
* add classifier head to donut
* add to transformers __init__
* add to auto model
* fix typo
* add loss for image classification
* add checkpoint
* remove no needed import
* reoder import
* format
* consistency
* add test of classifier
* add doc
* try ignore
* update loss for all swin models
* fix tests and some clean up
* make one general test for each modality
* remove redundant merging of kwargs
* edge cases
* dont enforce slow when reloading
* fix gemma3 tests
* has to adapt llama 4 after rebase
* remove also from overriden tests
* should be green now
* add peft model in constant
* add test
* fix formating
* make fixup execute
* change code
* check by self.task
* add test
* fixup test code
* fix minor typo
* fix pipeline test
* apply maintainers reqests
* add changed
* Revert "add changed"
This reverts commit 0a0166a1fe.
* update with NEW MODEL class called GLM4
* update
* Update glm4.md
* Name
* style
* fix copies
* fixup test
---------
Co-authored-by: Yuxuan Zhang <2448370773@qq.com>
* More limited setup -> setupclass conversion
* make fixup
* Trigger tests
* Fixup UDOP
* Missed a spot
* tearDown -> tearDownClass where appropriate
* Couple more class fixes
* Fixups for UDOP and VisionTextDualEncoder
* Ignore errors when removing the tmpdir, in case it already got cleaned up somewhere
* CLIP fixes
* More correct classmethods
* Wav2Vec2Bert fixes
* More methods become static
* More class methods
* More class methods
* Revert changes for integration tests / modeling files
* Use a different tempdir for tests that actually write to it
* Remove addClassCleanup and just use teardownclass
* Remove changes in modeling files
* Cleanup get_processor_dict() for got_ocr2
* Fix regression on Wav2Vec2BERT test that was masked by this before
* Rework tests that modify the tmpdir
* make fix-copies
* revert clvp modeling test changes
* Fix CLIP processor test
* make fix-copies
* 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>
* switch to use Expectations
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* extract gen bits from architecture and use it
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* add cross refererence
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* github why you do this
* fix
* make fixup
* disable cpu offload test
* fixup
* tmp reworks
* git branch movement
* make fixup
* add require_fsdp_v2_version
* dep issues
* update ruff and fixup
enable 2 types of case on XPU 1. test_resize_tokens_embeddings_with_deepspeed_multi_gpu 2. test_resize_embeddings_untied_with_deepspeed_multi_gpu
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* Remove unnecessary masked_fill in deberta models
* Enable some code when exporting but not compiling
* add missing import
* style
* replace if by torch.cond
* style
* use numel
* style
* add unit tests
* style
* change empty value for dynamic cache
* replace != [] by numel()
* fix import issue
* style
* Update Siglip attention implementation
* Update tests for Siglip
* Remove one level of indentation
* Update test to be more specific
* Fixup
* Idefics2
* Idefics3
* Emu3
* SmolVLM
* Phi4 (just init small update)
* Idefics2 (test fix)
* Update siglip2 tests
* Update eager
* trigger
* Clean up
* Transfer inputs to device in test
* Fixing test
* Fixing test
* Revert contiguous
* Remove unused is_flash_attn_2_available
* Move flaky to specific models
* 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>
* Never save 'reference_compile' config; should be set based on end user
* Reformat (I ran 'make style' from the wrong env)
* Use pop instead of del
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Use pop instead of del
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
---------
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* add gpt2 test on XPU
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* auto dtype has been fixed
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* convert model to train mode
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
---------
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* Initial commit for Qwen3
* fix and add tests for qwen3 & qwen3_moe
* rename models for tests.
* fix
* fix
* fix and add docs.
* fix model name in docs.
* simplify modular and fix configuration issues
* Fix the red CI: ruff was updated
* revert ruff, version was wrong
* fix qwen3moe.
* fix
* make sure MOE can load
* fix copies
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
* init commit
* style
* take comments into account
* add deepseekv3 modeling
* remove redundant code
* apply make style
* apply fix-copies
* make format
* add init files
* rename deepseekv3 into deepseek_v3 based on its model_type
* rename deepseekv3 into deepseek_v3 based on its model_type
* deepseek-v3 not deepseek_v3
* set model_type as deepseek_v3
* use default docs
* apply make
* fill type and docstring
* add rope_config_validation
* use custom DeepseekV3MLP
* hold code only for checkpoints congifuration; remove redundant
* revise rope yarn for DeepSeek variation
* rename DeepSeek-V3
* some refactoring
* revise load_hook to work properly; make moe func trainable; use llama instead of mixtral
* fix attention forward
* use -1 for not-changing dim when to use exapnd
* refactor DeepseekV3TopkRouter
* use reshape_for_rope instead of load_hook; revise attention forward for TP; rename q_head_dim with qk_head_dim
* register pre_hook and hook both
* make style
* use n_shared_experts
* Update src/transformers/models/deepseek_v3/configuration_deepseek_v3.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add test file
* update modeling_file according to modular file
* make style
* add mapping for DeepseekV3ForSequenceClassification
* remove aux_loss_alpha
* add deepseek_v3 for perf
* add deepseek_v3
* rename test as deepseekv3
* use tiny-deepseek-v3
* remove DeepseekV3ForSequenceClassification
* cache before padding
* remote output_router_logits
* Revert "remote output_router_logits"
This reverts commit f264f800d0.
* remove output_router_logits
* make e_score_correction_bias as buffer
* skip tests not compatible
* make style
* make e_score_correction_bias as buffer
* use rope_interleave instead of load_hook
* skip tests not compatible with MLA
* add doc for rope_interleave
* fix typo
* remove torch.no_grad for selecting topk
* fix post merge issue
* mrege with main and simplify
* nits
* final
* small fixes
* fix
* support TP better
* stash
* changes currently requires
* remove synch
* more fixes for TP
* temp fix for TP : some attention layers's FP8 scales are too small + shared is local colwise and anything is local if FP8 because weights are used
* updates to have generation work!
* push most of the changes
* reorder functions + call for contributions!
* update readme
* nits
* update
* ruff was updated on main
* merge with main and fix copies
* revert unrelated changes
* route all tokens to all experts when testing to avoid no gradient iddues
* finish fixing all tests
* fixup
* nit
* clean config
* last readme changes
* nit
* do cnit
* typo
* last nit
* one more one more
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: arthur@huggingface.co <arthur@ip-26-0-165-131.ec2.internal>
* Optimize to_py_obj for python-native numeric lists and scalars
* Fix bug that tuple is not converted to list
* Try np.array for more robust type checking
* Apply review and add tests for to_py_obj
* add audio chat templates
* update
* update
* nit
* green ci
* we dont care about the order anymore
* clean up after rebase
* overriden tests rename
* rename shieldgemma also
* one more rename
* require_read_token
* removde images/videos
* retrigger CI flaky
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: fix typos in test codes
* chore: format codes
* Added support for seed in `DataCollatorForWholeWordMask`, and also wrote tests.
Also fixed bugs where the code hardcoded values for mask replacement probability and random replacement probability, instead of using the values passed by the user.
* formatting issues
* Used better way to generate seed in TF. Made tests more consistent.
* process flattened images in fast image proc
* process flattened images in low proc and add tests
* remove print
* add unbalanced batch test pas image proc
* fix integration tests
